Computer-implemented systems and methods including language models for explaining and resolving code errors. A computer-implemented method may include: receiving one or more user inputs identifying a data set and providing a first user request to perform a first task based on at least a portion of the data set, wherein the data set is defined by an ontology; using a large language model (“LLM”) to identify a first machine learning (“ML”) model type from a plurality of ML model types; using the LLM to identify a first portion of the data set to be used to perform the first task; using the LLM to generate a first ML model training configuration; and executing the first ML model training configuration to train a first custom ML model, of the first ML model type, to perform the first task.
Systems and methods for developing one or more applications associated with a browser-based user interface within a multi-developer computing platform employ one or more processors that receive a request to build one or more applications configured to run in a browser-based user interface on a client; determine whether the one or more applications are associated with a core library and one or more runtime libraries; and in response to determining that the one or more applications are associated with the core library and the one or more runtime libraries: determine one or more version numbers associated with the one or more runtime libraries; and in response to the determined one or more version numbers being within a predetermined range associated with the core library, dynamically link the one or more runtime libraries and the one or more applications.
A system for query execution planning over ontology-based databases and related methods are disclosed. The system is programmed to receive an ontology query from a user account against an ontology having access controls, and transform the ontology query into a set of database queries, including a plurality of joins. The system is programmed to compute the amounts of data processing associated with executing the plurality of joins in different orders on a sample of the databases representing the ontology, considering how much data in the ontology can be accessed by the user account under the access controls, and determine an execution plan corresponding to a preferred amount of data processing. Furthermore, the system is programmed to execute the set of database queries on the databases according to the execution plan, and transmit a reply to the ontology query to the user device based on a result of the execution.
Systems and methods are provided for one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the system to perform: receiving successive frames of sensor data, the successive frames comprising a first frame and a second frame; determining transformations, in sensor coordinates, between coordinates of corresponding elements in the successive frames; determining a mapping between the transformations in sensor coordinates and transformations in geospatial coordinates of the corresponding elements in the successive frames; and determining second geospatial coordinates of the corresponding elements of a third frame based on: a transformation between the second frame and the third frame, and the mapping.
Systems, computer program products, and computer-implemented methods for generating interactive graphical user interfaces, software-based workflows, and data integrations using catalogs of workflow applications and auto-generation of aspects of the workflows. A method of the disclosure may include accessing one or more data stores that store: information indicative of one or more data sources, information indicative of one or more data object types, information indicative of one or more applications, and information indicative of compatibilities between the one or more data object types and the one or more applications; receiving a first user input indicating an association between a first data source and a first data object type; and based on the compatibilities and the indicated association, automatically populating each of the one or more applications that is compatible with the first data object type with data from the first data source, wherein populating includes generating interactive graphical user interfaces.
A system of a server is associated with channels, a plurality of client devices subscribed to the channels, and the server includes: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the system to perform operations comprising: receiving a system configuration change request from a client device, wherein the system configuration change request comprises a first system configuration file and channel information of a first channel; obtaining, based on the channel information, a second system configuration file that is currently deployed on client devices subscribed to the first channel; displaying, on a graphic user interface, a file comparison result between the first system configuration file and the second system configuration file; and in response to the file comparison result being verified, storing the first system configuration file in a request queue for the client devices to poll and deploy.
H04L 41/0853 - Retrieval of network configurationTracking network configuration history by actively collecting configuration information or by backing up configuration information
7.
PROVIDING AN OBJECT-BASED RESPONSE TO A NATURAL LANGUAGE QUERY
A data analysis system presents a user interface to allow a user to provide a natural language query pertaining to a dataset, wherein the dataset is associated with a data object model comprising a plurality of objects and receives, via the user interface, user input specifying the natural language query. The data analysis system further modifies, in the user interface, the user input to visually indicate one or more portions of the natural language query that each represent one of the plurality of objects and presents, in the user interface, a response to the natural language query, the response being based on data from the dataset, the data corresponding to the one of the plurality of objects.
A package manager used with a containerization platform can organize code portions into immutable layers. Collections of layers can be organized and saved together as an executable unit. Disclosed solutions recognize that because layers do not change, they can be reused by the same user and can also serve as shared building blocks for multiple environments running simultaneously. To facilitate sharing layers, a system can analyze which ones are common to multiple environments and allow multiple simultaneous environments to share common layers. Layer compression and dominator algorithms can be used to address inherent layer constraints. To facilitate use of existing layers for efficient start-up, code packages can be organized into base layers and additional layers, and commonly-used layers can be cached. A just-in-time approach can combine layers into new images on the fly and cache the new images for later use.
In some examples, systems and methods for checking data access are provided. For example, a method includes: receiving a checking request about a user, the checking request including a user identifier of the user and a resource indication of a resource; determining one or more components referenced by the resource; for each component of the one or more components referenced by the resource, determining permission information indicating whether the user access to at least a part of the one or more components; and determining permission information indicating whether the user is permitted to access the resource.
An example method of determining geolocations of composite entities based on information retrieved from heterogeneous data sources comprises: identifying, by a computer system, an association of a first object and a second object with a composite object; receiving, from a first data source associated with the first object by an ontology, a first dataset including a first data item specifying a first time identifier and a first geolocation associated with the first object; receiving, from a second data source associated with the second object by the ontology, a second dataset including a second data item specifying a second time identifier and a second geolocation associated with the second object; and determining, by applying a rule set associated with the ontology to the first dataset and the second dataset, a geolocation of the composite object and a corresponding time identifier.
A method comprises storing, in a build catalog, for each update of a dataset, an entry including a branch identifier, an identifier and a version of the dataset, and build dependency information; receiving a first request to build a second branch having a first branch as a parent branch, the first branch being associated with a first version of a first driver program for building a first dataset from a set of child datasets, the second branch being associated with a second version of the first driver program; determining that the second branch does not have any version of a specific child dataset based on the build catalog; retrieving a latest version of the specific child dataset from the first branch; causing a build of the first dataset based on the latest version of the specific child dataset and the second version of the first driver program.
A computer system is disclosed that provides classification-based access controls at the dataset row-level. The system may perform operations including: ingesting a dataset, wherein the dataset comprises a table of rows and columns; determining a column of the table that includes permissions information; applying parsing rules to the column to determine, for each row of the table, a list of permissions markings; receiving, from a user, a request to access the dataset; and in response to receiving the request: determining a permissions policy associated with the user; determining an evaluated policy associated with the user based on the permissions policy; filtering the table based on applying the evaluated policy associated with the user to the permissions markings of each row of the table; and providing the user access to the filtered table.
In some examples, systems and methods for disaggregating a set of documents are provided. An example method includes receiving the set of documents. In some examples, the set of documents include a plurality of pages. In some examples, the method further includes extracting a plurality of content items from the plurality of pages and providing the plurality of extracted content items to a machine-learning model. In some examples, the machine-learning the model is trained to generate content vectors. In some examples, the method further includes receiving, from the machine learning model, a plurality of content vectors corresponding to the plurality of extracted content items, determining, for each page of the plurality of pages, a plurality of potential nearest labelled pages in one or more labelled documents and a plurality of vector distances from the plurality of potential nearest labelled pages, based on the plurality of content vectors, and determining a segmentation option based at least in part on the plurality of vector distances. In some examples, the segmentation option indicates that a group of pages in the plurality of pages belong to a specific document.
Computing systems methods, and non-transitory storage media are provided for obtaining a request or query indicative of a resource, tool, task, or workflow, determining any entities including data, logic, dependencies and libraries, within a remote server, corresponding to the resource, tool, task, or workflow, and selectively provisioning or caching, from the remote server, the entities at the computing system.
A system for automated processing and analysis of audio files for large data sets in a cloud environment. A unified analytic environment can integrate audio machine learning models for processing and analysis with a knowledge management system, including graph presentations of tracked entities, linked to audio files and/or associated translations and transcripts. Entities within such data can be searched or filtered and proposed for tracking, or identified as tracked objects. These features can allow triage and prioritization of audio files for analysis. User interfaces can facilitate feedback on transcription and translation outputs, thereby improving present outputs and future inputs and outputs. Entities speaking or referred to can be found, tagged, and distinguished in audio files (e.g., using speaker identification in audio files, text searching in transcripts, etc.) Users can provide feedback and input on various aspects of a system, to enhance or adjust initial automated or other machine learning outputs.
A method comprises obtaining a prompt indicating that when a user query satisfies a set of criteria, the user query is to be translated into a set of graph queries in a graph query language; receiving a specific user query in natural language indicating access to an ontology and satisfying the set of criteria, data of the ontology being stored in one or more databases, including a graph database; incorporating the specific user query into the prompt to obtain an extended prompt; executing, with the extended prompt, a first large language model; obtaining, from the executing, a set of database queries including one or more graph queries in the graph query language to access the ontology; submitting the set of database queries to a set of databases to obtain a database query result; transmitting the database query result in response to the specific user query.
Systems, methods, and non-transitory computer readable media are provided for displaying and annotating map-based geolocation data at an augmented reality (AR) headset. Users with access to the map-based geolocation data can create or confirm annotations for geospatial data that may be sent to the server computer and transmitted back to the headset of the user as well as different AR headsets associated with other users.
G06F 16/783 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G01C 21/20 - Instruments for performing navigational calculations
Streaming of shared state date from a presenter device to one or more viewer devices may be accomplished by shared state of a file (e.g., state of a presentation and/or the application that is displaying Information from the file and/or data related to the particular shared streaming of the presentation) rather than a screen share view of the application and/or file.
H04L 65/401 - Support for services or applications wherein the services involve a main real-time session and one or more additional parallel real-time or time sensitive sessions, e.g. white board sharing or spawning of a subconference
G06Q 10/101 - Collaborative creation, e.g. joint development of products or services
A method comprises receiving a set of data source updates for datasets; transforming the set of data source updates to a list of updates to an ontology, the ontology including a definition for each ontology entity type that include one or more properties, obtaining a first transformation mapping columns of a first dataset to a first set of properties of a certain ontology entity type; obtaining a second transformation mapping columns of a second dataset to a second set of properties of the certain ontology entity type; obtaining a specific security policy that applies to the first set of properties based on a first set of permissions controlling access to rows of the first dataset; obtaining a particular security policy that applies to the second set of properties based on a second set of permissions controlling access to rows of the second dataset.
A system for efficient query execution over ontology-based databases and related methods are disclosed. The system is programmed to receive an ontology query from a user account against an ontology having access controls, and transform the ontology query into a set of database queries, including a set of exact aggregations or joins. The system is programmed to then estimate how much data processing is to be performed in executing the set of exact aggregations or joins, considering how much data in the ontology can be accessed by the user account under the access controls. Upon determining that the estimated amount of data processing exceeds a threshold, the system is programmed to route the set of exact aggregations or joins to a set of nodes optimized for large-scale data processing.
A method, performed by one or more processors, including: receiving one or more event records; generating, using the one or more event records, an event descriptor object descriptive of one or more events occurring in a networked system, wherein the event descriptor object comprises a plurality of event properties; receiving one or more entity records; generating, using the one or more entity records, an entity descriptor object descriptive of one or more entities relevant to the security of the networked system, wherein the entity descriptor object comprises a plurality of entity properties; incorporating, into an object graph, the event descriptor object and the entity descriptor object; and associating, in the object graph, the event descriptor object with the entity descriptor object using at least one of the plurality of event properties and at least one of the plurality of entity properties.
A data analysis system is disclosed that receives data from a master data system to enable useful and efficient rescheduling of items, taking into account effects of various rescheduling options on various metrics related to the items and/or the scheduling. The data analysis system includes sophisticated data analysis and interactive graphical user interface functionality to enable efficient, multi-variable evaluation of various rescheduling options. The interactive graphical user interface includes interactive functionality for suggesting rescheduling options in view of the effects of those changes on various metrics, evaluating various rescheduling options in view of effects on the various metrics, adjusting instances of metrics related to items/timelines in view of scheduling changes, and the like. Once a set of schedule modifications are determined by the data analysis system, the data analysis system can push the schedule modifications back to the master data system for implementation.
Disclosed are systems and methods for validations related to software. In some embodiments, a method for building software with software action validations, the method comprising: accessing a target object type, the target object type comprising one or more object properties; accessing an action type, the action type comprising one or more action parameters, the action type associating with editing a target object of the target object type; generating a set of validation rules associated with the action type, wherein the set of validation rules comprise a local validation rule associated with a rule parameter; and building a software application, wherein the software application comprises the target object type, the action type, and the set of validation rules.
Systems and methods for identifying associations between a code snippet query and stored computer code stored. The method can receive a code query identifying a code snippet to search for, determine a fingerprint of the query code snippet, and search the stored software using the fingerprint to identify software results of code similar to the query code snippet. The fingerprint can be determined by generating k-grams of the code snippet. The k-grams used for the search can be down-selected based on a winnowing process. The method can remove from the software results code that is associated with sanctioned software. The method can include coalescing the software results to produce a subset of the software results, generating a code search user interface comprising information indicative of the subset of software results, and causing presentation of the code search user interface and displaying the subset of software results.
Computer implemented systems and methods are disclosed for importing data from electronic data files. In accordance with some embodiments, source electronic data files are received at a data importation system and managed by the data importation system. The data importation system may apply detector/transformer plugins to the received source electronic data files to transform the files for importation into one or more data analysis systems and/or databases. The data importation system may also receive user inputs for mapping source electronic data files to transformation templates. The inputs may include, for example, an assignment of a file format to the source electronic data file, identification of a file type identifier associated with the source electronic data file, and a mapping of a the source electronic data file to a transformation template. The data importation system may store the received inputs as a file type profile in a database.
A method of automatic modification of repository files comprises applying a first check of a plurality of checks to a first source file in a repository, the first check including instructions to automatically modify code based on predetermined scripts or configurations; determining that applying the first check to the first source file generates a first differential output; automatically requesting the repository to transmit a request for confirming merging changes represented in a first differential output into the first source file; applying a second check of the plurality of checks to the first source file; determining that applying the second check to the first source file results in generating a second differential output; automatically approving merging changes represented in the second differential output into the first source file.
In some examples, systems and methods for managing data access are provided. For example, a method includes: receiving a data access request for a user, the data access request including a resource indication of a data resource; providing the user a membership of an access group associated with the data resource; determining a member temporal parameter associated with the data resource based on one or more temporal parameters associated with the access group; and associating the member temporal parameter with the user.
Aspects of the present disclosure relate to mapping content delivery. A client device provides, to a map management server, a request for a map of a geographic region. The client device receives, from the map management server, an identification of tiles for the map. The client device provides, to a first tile server, a request for the tiles for the map. In response to receiving the tiles from the first tile server: the client device displays the map of the geographic region based on the tiles.
In some examples, systems and methods for managing access control to one or more resources are provided. An example method includes receiving a permission request for a user to access the one or more resources, generating an access request based at least in part on the permission request, notifying one or more reviewers to review the access request, receiving an indication of the access request being approved, and automatically granting permission to the user to access the one or more resources.
A method and system for collaborative data management within a multi-source data collaboration platform are disclosed. The system receives data objects from various sources through a plurality of Application Programming Interfaces (APIs) and stores them into a system branch. Upon receiving user editorial requests to edit or add data objects, the system forks user branches from the system branch to execute these requests. The graphical user interface (GUI) displays both the system branch and user branches, allowing users to fork additional branches as needed. Prediction results are generated based on data from both the system branch and user branches, enabling users to compare and analyze different sets of predictions. This collaborative approach facilitates efficient data management and analysis, enhancing decision-making processes across multiple users and branches within the platform.
In some examples, systems and methods for managing task approvals are provided. An example method includes receiving a task identifier for a task that is requested to be approved, and one or more subtasks decomposed from the task, and generating a task request including a task request identifier. In some examples, the task request is associated with the task, the task request identifier corresponds to the task identifier, and each subtask of the one or more subtasks of the task corresponds to one or more approval policies. In some examples, the method further includes: determining, for each subtask of the one or more subtasks of the task, whether the one or more approval policies are satisfied, in response to determining that, for each subtask of the one or more subtasks of the task, the one or more approval policies are satisfied, approving the task, and outputting an indication of the approval.
An approach for transforming a large dataset using user interface-based transformations applied to a sample of the dataset is disclosed. The sample of the large dataset has the same or similar format as the large dataset. A user can quickly apply transformations to the sample dataset using UI-based instructions. The UI-based instructions can be used to create a transformation job that can be configured to run on a backed database, such as a distributed database, to apply the transformations to the large dataset.
A computer system is configured to receiving a data set from a data provider and automatically save the data set in a quarantine database where copying, moving, and sharing of the data set are restricted until the data set is released by a data provider. The data set is parsed to find and mark portions with potentially sensitive information. At least those parts are reviewed by a data governor, who can confirm, add, edit, or remove markers. Those parts can be visually indicated to the data governor, along with a preview of, metadata about, and analysis of the data set. After reviewing at least the automatically marked portions, the data governor can release the data set to a non-quarantine database where another user can use the data set. The user is restricted from accessing the quarantine database.
A method comprises importing a redacted graph, each node representing a data object, the redacted graph being redacted based on at least one access control classification, each edge representing one or more relationships between two data objects; assigning a new access control classification to the redacted graph independent of the at least one access control classification; determining that one or more nodes of the redacted graph represent one or more data objects stored on a local computing device; performing data deconfliction for the one or more data objects; updating the one or more nodes of the redacted graph to contain deconflicted data; identifying a portion of the redacted graph to be redacted for export based on one or more redaction criteria, including one related to the new access control classification; redacting the portion from the redacted graph to obtain an updated graph; exporting a machine-readable representation the updated graph.
An interactive data object map system is disclosed in which large amounts of geographical, geospatial, and other types of data, geodata, objects, features, and/or metadata are efficiently presented to a user on a map interface. The interactive data object map system allows for rapid and deep analysis of various objects, features, and/or metadata by the user. A layer ontology may be displayed to the user. In various embodiments, when the user rolls a selection cursor over an object/feature an outline of the object/feature is displayed. Selection of an object/feature may cause display of metadata associated with that object/feature. The interactive data object map system may automatically generate feature/object lists and/or histograms based on selections made by the user. The user may perform geosearches, generate heatmaps, and/or perform keyword searches, among other actions.
G06T 11/60 - Editing figures and textCombining figures or text
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/04842 - Selection of displayed objects or displayed text elements
A system for providing a unified query interface across multiple ontology-based databases and related methods are disclosed. The system is programmed to receive calls to an application programming interface for querying an ontology, where ontology data is represented in different databases respectively in different forms. For each function being called, system is programmed to select a database from the different databases based on the function type and each ontology entity type being processed by the function. The system is further programmed to retrieve data from each selected database, merge the retrieval results as appropriate, and transform the final result to ontology data in response to the calls.
In various example embodiments, a system and method for transforming instructions for collaborative updates are described herein. A group of instructions for an update of an element depicted in a client device version of a user interface are generated. The group of instructions is executed and the group or a subset of instructions are transmitted to a server. The server accepts or rejects the instructions. The server may execute the instructions to update a server version of the element. The server sends accepted instructions to the other or all client devices.
G06F 9/451 - Execution arrangements for user interfaces
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
A system for managing versioning of ontology data represented in multiple forms respectively in multiple databases and related methods are disclosed. The system is programmed to determine which changes to the ontology are to be incorporated into a new version of specific ontology data. In response to a write request to write a latest version of specific ontology data, the system is programmed to start representing the latest version in the multiple databases according to a first predetermined strategy. In response to a read request to read a latest version, the system is programmed to return a particular version from at least one of the multiple databases according to a second predetermined strategy.
In some examples, systems and methods for object pairings are provided. For example, a method includes: receiving an input associated with at least one of the one or more first values of one or more weights, the one or more weights corresponding to one or more model parameters associated with a task; determining one or more second values of the one or more weights, at least one second value of the one or more second values of the one or more weights being determined based at least in part on the input; modifying the machine-learning model based on the one or more second values of the one or more weights; determining a plurality of object pairings for the task by applying the modified machine-learning model to data associated with the task, each object pairing of the plurality of object pairings including an asset object and the target object.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for creating, implementing, and managing applications related to categorizing, managing, tracking, and analyzing the relationship between different blocks of data and data sets; Downloadable application programming interface (API) software for creating, implementing and managing applications related to categorizing, managing, tracking, and analyzing the relationship between different blocks of data and data sets; Downloadable software for implementing artificial intelligence and machine learning algorithms and programs concerning the categorization, management, tracking, and analysis of the relationships between different blocks of data and data sets
43.
SYSTEMS AND METHODS FOR PROVIDING CATEGORY-SENSITIVE CHAT CHANNELS
Systems, methods, and non-transitory computer readable media are provided for providing category-sensitive chat channels. A category-sensitive chat channel may be provided. The category-sensitive chat channel may be assigned a given category level. The given category level may determine a scope of content allowed in the category-sensitive chat channel. Information to be posted through the category-sensitive chat channel may be obtained. The obtained information may be filtered based on the given category level. The filtered information may be posted in the category-sensitive chat channel.
An explorer user interface allows users that are interested in making purpose-based access requests to datasets to view aggregated and/or summary data regarding available datasets prior to making the purpose-based access request. A guided discovery wizard allows a user to view summarized and/or general information regarding datasets and may provide the user options to filter the datasets based on such information and/or based on parameters of specific data items within the datasets (without exposing the specific data items to the user). Thus, the user may filter the datasets to determine a cohort of datasets including data items that are interesting or useful for the specific purpose. The system may provide access to a subset of filtered datasets for the specific purpose in a self-contained, dedicated-purpose directory (an “investigation workspace”) that includes only the precise portion of data that is needed for the requested purpose.
Computer-implemented systems and methods are disclosed, including for remotely modifying a configuration file defining a computing environment configuration. A computer-implemented may include, for example, receiving, from a remote server computing device, a configuration file defining a computing environment configuration, parsing the configuration file to generate an indexed data structure, the indexed data structure comprising location identifiers of characters of the configuration file, storing the indexed data structure, generating a graphical user interface based at least in part on the indexed data structure, receiving, via the graphical user interface, a user input indicating a modification to the computing environment configuration, determining, by reference to the indexed data structure and the location identifiers, and based on the user input, one or more changes to the configuration file, and communicating, to the remote server computing device, instructions to update the configuration file in accordance with the one or more changes.
Methods and systems for generating and analyzing visualizations based on a group of sets of data objects. One system includes processors executing instructions to present the sets of data objects in a selectable format on a display device, receive a user selection of a first set of data objects, generate a user interface comprising an indication of the first set of data objects and a plurality of selectable tools to generate a first data visualization of the first set of objects from one or more operations to the first set of objects, receive a user selection of a second set of data objects, receive a user selection to cause the application of the one or more operations to the second set of data objects, and update the user interface to comprise a second visualization based on the one or more operations performed on the second set of data objects.
A computer system can a canonical dataset, a buffer, and an edits dataset. The buffer can dump edits to the edits dataset responsive to one or more conditions. The system can receive a query of the canonical dataset and can rewrite the query to access data from the canonical dataset, the edits dataset, and/or the buffer. The system can execute the query on a combination of data from the canonical dataset, the edits dataset, and/or the buffer, including one or more edits to be made to the canonical dataset.
A computer system is disclosed that provides purpose-based control of user actions and access to electronic data assets. For example, the computer system may perform operations including: receiving, from a user, a request to perform an action; determining any checkpoint config objects associated with the action; displaying checkpoint dialog based on checkpoint config object; determining whether criteria associated with the checkpoint object are satisfied; and in response to determining that the criteria associated with the checkpoint object are satisfied: generating a checkpoint record object; and proceeding to perform the action.
A method for management of a production pipeline is disclosed. The method may comprise accessing a data model which comprises a plurality of data objects, including one or more assembly objects, each assembly object representing a part to undergo one or more production events to be performed on a part at a first party facility for providing to a second party facility and one or more production event objects, each production event object representing a particular production event and having a plurality of properties, including an associated start time property and an end time property. The method may also comprise receiving selection of one or more production event objects to be linked to a first assembly object and receiving input of one or more alert conditions to be linked to the first assembly object.
Methods, systems, and non-transitory computer readable media to display a geographical map overlaid with a marker layer comprising at least one marker; receive input from a user to change a zoom level of the geographical map from a first map scale to a second map scale; display the geographical map at the second map scale; and overlay the marker layer at the second map scale with the at least one marker at a second marker size. The second marker size is determined based on a correlation between the second map scale and the second marker size, in which (i) the second marker size is increased or decreased in the same direction as the second map scale when the second map scale is within a range from low threshold point to high threshold point.
G01C 21/36 - Input/output arrangements for on-board computers
G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
G06T 3/40 - Scaling of whole images or parts thereof, e.g. expanding or contracting
A search request relating to one or more datasets in the data repository can be received, the search request comprising a display request to display at least a portion of the one or more datasets. In response to the search request, a searchable database can be generated from the one or more datasets in a data repository based on ontological data associated with the one or more datasets. An object view of at least the portion of one or more datasets can be generated from the searchable database, the view being generated based on the ontological data. The generated object view can be provided to be displayed on a display device.
A system and method can provide charter-based access to resources using an object model. Charters are defined by an administrator to have certain markings, each marking indicating a control (e.g., permission, credential, qualification, constraint, requirement, etc.) that regulates work under the charter. Users are also associated with markings. A user starts a session to access the system and is authenticated. The system determines charters having markings that the user has, and these charters are provided to the user to select from. Selecting a charter allows the user access to resources associated with the charter, under the controls indicated by the markings. Charters, controls, qualifications, resources, authorizations and links between them can be implemented using an object model. Markings can control session parameters (e.g., geographic location), resource access, user credentials, qualifications, and/or data processing permissions for a group of users, simplifying project definition and revisions to controlling access under the charter.
A system is programmed to train or fine-tune a large language model (LLM) for converting a user query in natural language to database queries for accessing a set of databases where data related to an ontology is stored. The set of databases includes a graph database and stores metadata and actual data of the ontology. The system is further programed to receive a specific user query exploring links between objects in the ontology and leads to updates to the ontology. The system is programmed to then execute the LLM to obtain a set of database queries, including one or more graph queries. Furthermore, the system is programmed to submit the set of databased queries to the set of databases, which implements the updates to the ontology. The system is then programmed to receive data query results and transmit them in response to the specific user query.
SYSTEMS AND METHODS FOR GENERATING AND DISPLAYING A DATA PIPELINE USING A NATURAL LANGUAGE QUERY, AND DESCRIBING A DATA PIPELINE USING NATURAL LANGUAGE
System and method for generating and displaying data pipelines according to certain embodiments. For example, a method includes: receiving a natural language (NL) query; receiving a model result generated based on the NL query, the model result including a query in a standard query language, the model result being generated using one or more computing models; and generating the data pipeline based at least in part on the query in the standard query language, the data pipeline comprising one or more data pipeline elements, at least one data pipeline element of the one or more pipeline elements being corresponding to a query component of the query in the standard query language.
SYSTEMS AND METHODS FOR GENERATING AND DISPLAYING A DATA PIPELINE USING A NATURAL LANGUAGE QUERY, AND DESCRIBING A DATA PIPELINE USING NATURAL LANGUAGE
System and method for generating and displaying data pipelines according to certain embodiments. For example, a method includes: receiving a natural language (NL) query; receiving a model result generated based on the NL query, the model result including a query in a standard query language, the model result being generated using one or more computing models; and generating the data pipeline based at least in part on the query in the standard query language, the data pipeline comprising one or more data pipeline elements, at least one data pipeline element of the one or more pipeline elements being corresponding to a query component of the query in the standard query language.
Methods, systems, and apparatus, including computer programs encoded on computer storage media for data security protection are provided. One of the methods includes: receiving a job associated with a project, wherein the project is associated with one or more data sources; identifying a plurality of inputs and a plurality of outputs associated with the job; determining a plurality of required permissions associated with the job, wherein each of the required permissions comprises an operation on a required data source, the operation corresponding to at least one of the inputs or the outputs; verifying that the one or more data sources associated with the project comprise the required data source associated with each of the required permissions; and generating a token associated with the job, the token encoding the required permissions associated with the job, wherein the token is required for execution of the job.
In some examples, systems and methods for systems integration are provided. For example, a method includes: receiving a first data asset in a first data format from a first data source; receiving a second data asset in a second data format from a second data source, the second data format being different from the first data format, the second data source being different from the first data source; performing a correlation process to merge the first data asset in the first data format and the second data asset in the second data format to generate a unified data asset in a common data format, the common data format being different from the first data format, the common data format being different from the second data format; and providing the unified data asset in the common data format to a plurality of software applications.
A method performed by one or more processors comprises displaying code, receiving user selection of a portion of code, determining one or more settable data items, generating a template, displaying the template, receiving a user input value for the settable data items by the template, and executing the code with each of the settable data items set to the received user input value. A data processing pipeline is configured to pass a data item to a first transformer to provide first transformed data, store the first transformed data in a temporary memory, write the first transformed data to the data storage system, and pass the transformed data from the temporary memory to a second transformer.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for edge computing, namely, downloadable software for processing data via a distributed computing framework; downloadable edge software using artificial intelligence for processing data via a distributed computing framework; downloadable software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; downloadable software for artificial intelligence for use in machine learning, deep learning, natural language generation, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics, business intelligence, and computer vision; downloadable software for knowledge-based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics and business intelligence; downloadable simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; downloadable software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of data and information; downloadable hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; downloadable software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of geospatial, map and location data and information; downloadable hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; downloadable software for use in advance product research; downloadable computer software development tools; downloadable software for creating, managing, and utilizing ontologies to drive and enable business and operational decisions and actions, workflows, organizational modeling, simulated operations, and collaborative operations and applications; downloadable software for general ledger management; downloadable software for product lifecycle management; downloadable software for enterprise resource planning; downloadable manufacturing execution system software; downloadable software for customer relationship management (CRM); downloadable software for material resource planning; downloadable software for generating, analyzing, and managing data related to engineering bills of materials; downloadable software for generating, analyzing, and managing data related to manufacturing bills of materials; downloadable software for collecting, managing, analyzing, transmitting, storing, sharing, and optimizing the transfer of data over disconnected, denied, intermittent, and limited (DDIL) bandwidth environments; downloadable software for evaluating organizations, determining whether the organizations confirm to established computer security standards, cybersecurity maturity model standards, and data management standards, and for sharing and verifying the aforesaid information; downloadable business process improvement software for optimizing and streamlining manufacturing operations and related maintenance activities; downloadable business process improvement software for optimizing and streamlining digital manufacturing operations and related maintenance activities; downloadable software for vehicle fleet management; downloadable artificial intelligence software for generating real-time insights and operational efficiencies to assist users in scaling manufacturing operations and optimizing related production, supply chain, and logistics functions; downloadable business productivity software for scheduling and workplace collaboration; downloadable software for customizing, maintaining, updating, installing, and deploying other software; downloadable project management software; downloadable software for auditing business activities and business data to facilitate regulatory compliance Business data analysis; business consulting services concerning use of data and information by financial institutions, health institutions, non-profit organizations, legal institutions, commercial entities, and government agencies; business data and information consulting services Providing temporary use of online non-downloadable software for edge computing, namely, for processing data via a distributed computing framework; providing temporary use of online non- downloadable edge software using artificial intelligence software for processing data via a distributed computing framework; providing temporary use of online non-downloadable software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; providing temporary use of online non-downloadable artificial intelligence software for machine learning, deep learning, natural language generation, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics, business intelligence, and computer vision; providing temporary use of online non-downloadable software, namely, non-downloadable software for knowledge- based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics and business intelligence; providing temporary use of online non-downloadable simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; providing temporary use of online non-downloadable software for artificial intelligence, namely, for use in data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, machine learning, deep learning, natural language generation, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics, business intelligence, and computer vision; providing temporary use of online non-downloadable knowledge-based artificial intelligence software platforms, data analytics software platforms, and automation software platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics and business intelligence; advanced product research; providing temporary use of online non-downloadable software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of data and information; providing temporary use of online non-downloadable software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of geospatial, map and location data and information; providing temporary use of online non-downloadable software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; scientific and technological services, namely, scientific research; scientific and technological research and development; information technology consultation and research; custom software engineering services and software design; software design and development; providing temporary use of online non-downloadable hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; providing temporary use of online non-downloadable software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of geospatial, map and location data; providing temporary use of online non- downloadable software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; providing temporary use of online non-downloadable software development tools; providing temporary use of online non-downloadable software featuring software platforms for creating, managing, and utilizing ontologies to drive and enable business and operational decisions and actions, workflows, organizational modeling, simulated operations, and collaborative operations and applications; providing temporary use of online non-downloadable software for general ledger management; providing temporary use of online non-downloadable software for product lifecycle management; providing temporary use of online non-downloadable software for enterprise resource planning; providing temporary use of online non-downloadable manufacturing execution system software; providing temporary use of online non-downloadable software for customer relationship management (CRM); providing temporary use of online non-downloadable software for material resource planning; providing temporary use of online non-downloadable software for generating, analyzing, and managing data related to engineering bills of materials; providing temporary use of online non-downloadable software for generating, analyzing, and managing data related to manufacturing bills of materials; providing temporary use of online non-downloadable software for collecting, managing, analyzing, transmitting, storing, sharing, and optimizing the transfer of data over disconnected, denied, intermittent, and limited (DDIL) bandwidth environments; providing temporary use of online non-downloadable software for evaluating organizations, determining whether the organizations confirm to established computer security standards, cybersecurity maturity model standards, and data management standards, and for sharing and verifying the aforesaid information; providing temporary use of online non-downloadable business process improvement software for optimizing and streamlining manufacturing operations and related maintenance activities; providing temporary use of online non-downloadable business process improvement software for optimizing and streamlining digital manufacturing operations and related maintenance activities; providing temporary use of online non-downloadable software for vehicle fleet management; providing temporary use of online non-downloadable artificial intelligence software for generating real-time insights and operational efficiencies to assist users in scaling manufacturing operations and optimizing related production, supply chain, and logistics functions; providing temporary use of online non-downloadable business productivity software for scheduling and workplace collaboration; providing temporary use of online non-downloadable software for customizing, maintaining, updating, installing, and deploying other software; providing temporary use of online non-downloadable project management software; providing temporary use of online non-downloadable software for auditing business activities and business data to facilitate regulatory compliance
Systems, methods, and non-transitory computer readable media are provided for generating or obtaining situations in which scores indicative of a danger or a hazard exceeds a threshold, receiving a selection of a first situation, in response to receiving the selection of the first situation, obtaining intelligence data, asset data, and operational data, analyzing the intelligence data using a trained machine learning model for the first situation; and determining a response measure based on the analyzed intelligence data.
A system comprising a computer-readable storage medium storing at least one program and a method for integrating collaborative spreadsheet data into one or more network applications is presented. The method may include accessing an application data schema comprising a set of constraints on application data consumed by an application hosted by an application server. The method may further include accessing a spreadsheet having one or more data validation rules. The method may further include determining whether the one or more data validation rules include the set of constraints. In response to determining the one or more data validation rules include the set of constraints, application data consumed by the application is synchronized with spreadsheet data corresponding to the spreadsheet.
G06F 40/18 - Editing, e.g. inserting or deleting of tablesEditing, e.g. inserting or deleting using ruled lines of spreadsheets
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
A computer system is disclosed that provides purpose-based access to electronic data assets. For example, the computer system may perform operations including: receiving, from a first user, a request to access data assets associated with a purpose object; in response to receiving the request from the first user: generating a purpose access request object including at least an identification of the first user and an identification of the purpose object; and providing an indication of the purpose access request object to a second user associated with the purpose object; receiving, from the second user, an approval of the request; and in response to receiving the approval of the request from the second user: updating the purpose access request object to include at least an indication of the approval of the request; and granting the first user access to data assets associated with the purpose object.
A method of managing digital entities in data repositories comprises storing one or more data objects in a non-graph data repository into one or more nodes and edges of a graph, comprising transforming an access control list (ACL) of a first data object into an ACL node and transforming a version of a second data object into a version node in a graph data repository; electronically receiving a search query associated with a user account for a shortest path between two specified nodes of the graph; executing the search query against the graph data repository to generate a result set of nodes including only nodes corresponding to most recent versions of the one or more data objects that are visible to the user account under applicable ACLs.
Example embodiments involve a metrics collection system for collecting software usage metrics from one or more client devices at deployments. A computer, such as a server configured to execute the metrics collection system, collects software usage metrics (e.g., as a metrics submission from a client device) of the software product at the deployment, identifies a metrics type of the software usage metrics collected, assigns the software usage metrics to a metrics category, and calculates and updates a metrics score of the metrics category, based on the software usage metrics collected.
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Methods and systems for enhanced techniques for building user interfaces. An example method includes presenting a builder user interface to create a consumer user interface. The builder user interface receives information usable to filter data objects associated with a data object type. The information includes a variable associated with a property indicated by the data object type and the variable is associated with a first user interface element of the consumer user interface. An association between a second user interface element included in the consumer user interface and presentation of information generated based on data objects is received. Adjustment of the first user interface element causes filtering of the data objects via adjustment of the variable updating of the information. Access to the consumer user interface is enabled.
G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 16/9035 - Filtering based on additional data, e.g. user or group profiles
68.
SYSTEMS AND METHODS FOR GENERATING AND DISPLAYING A DATA PIPELINE USING A NATURAL LANGUAGE QUERY, AND DESCRIBING A DATA PIPELINE USING NATURAL LANGUAGE
System and method for generating and displaying data pipelines according to certain embodiments. For example, a method includes: receiving a natural language (NL) query; receiving a model result generated based on the NL query, the model result including a query in a standard query language, the model result being generated using one or more computing models; and generating the data pipeline based at least in part on the query in the standard query language, the data pipeline comprising one or more data pipeline elements, at least one data pipeline element of the one or more pipeline elements being corresponding to a query component of the query in the standard query language.
Computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for generating data objects and/or updating an ontology. A computer-implemented method may include: employing one or more large language models (“LLMs”) to generate at least a data triple and a classified triple; executing, using the classified triple, a similarity search with reference to an ontology to determine that the classified triple at least partially matches one or more data object types defined in the ontology; in response to the determination, adding into a first database at least a first data object of a first data object type that represents a first entity in the data triple and a second data object of a second data object type that represents a second entity in the data triple.
G06F 18/2415 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
G06N 3/0895 - Weakly supervised learning, e.g. semi-supervised or self-supervised learning
70.
RESOURCE DEPENDENCY SYSTEM AND GRAPHICAL USER INTERFACE
A resource dependency system and its associated user interfaces, used for tracking data dependencies and data transformations between resources, may display visual node graphs with resources as nodes and the data dependencies and data transformations associated with the columns as edges between the nodes. The nodes representing the resources may be displayed differently based on relevant differences in the resources they represent, which can be set through various selectable criteria and schemes.
G06F 16/909 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
G06N 7/01 - Probabilistic graphical models, e.g. probabilistic networks
G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
Aspects of the present disclosure relate to computer system security. A machine accesses a set of records corresponding to a set of users having access to a computer system. The machine stores, for each user in the set of users, a baseline profile representing baseline activity of the user with respect to a set of data sources of the computer system. The machine monitors activity of the set of users with respect to the set of data sources. The machine determines, based on monitoring the activity of the set of users, that a user action of a specified user, with respect to one or more data sources from the set of data sources, is anomalous relative to the baseline profile of the specified user. The machine provides a digital transmission representing the anomalous user action.
Disclosed herein are systems and methods for generating notional data. The method includes: receiving seed data of one or more object types in a base dataframe; defining one or more functional relationships associated with the one or more object types, at least one functional relationship of the one or more functional relationships specifying a change to seed data of one object type of the one or more object types; generating data of the one or more object types based at least in part on the seed data in the base dataframe and the one or more functional relationships; and generating the notional data based at least in part on the generated data of the one or more object types.
Systems and methods are provided for coordinating the deployment of frontend assets to defined user groups. Individual groups of users may be assigned to a track comprising a set of frontend assets. Each set of frontend assets may comprise each of the individual components required to generate an entire frontend for an application. In some embodiments, different versions of a single component may be assigned within different tracks. As such, one set of users may be provided a first version of an application and a second set of users may be provided a second version of that application. By associating a new or updated version of a component to a given track, a new or updated version of a component not yet ready for widespread deployment may be provided to only a limited number of users.
Methods and systems for providing a user interface and workflow for interacting with time series data, and applying portions of time series data sets for refining regression models. A system can present a user interface for receiving a first user input selecting a first model from a list of models for modeling the apparatus, generate and display a first chart depicting a first time series data set depicting data from a first sensor, generate and display a second chart depicting a second time series data set depicting a target output of the apparatus, receive a second user input of a portion of the first time series data set, and generate and display a third chart depicting a third time series data set depicting an output of the selected model and aligned with the second chart of the target output and updated in real-time in response to the second user input.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Business data analysis; business consulting services concerning use of data and information by financial institutions, health institutions, non-profit organizations, legal institutions, commercial entities, and government agencies; advisory services relating to information and data processing Providing non-downloadable operating system software; providing non-downloadable software using artificial intelligence to empower integration of data, operations and decision-making; providing non-downloadable software for edge computing; providing non-downloadable edge artificial intelligence software; providing non-downloadable software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; providing non-downloadable software for artificial intelligence, machine learning, deep learning, natural language generation, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics, business intelligence, and computer vision; providing non-downloadable software, namely, knowledge-based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics and business intelligence; providing non-downloadable simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; providing non-downloadable software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, hosting, security, and tracking of data and information; providing non-downloadable software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, hosting, security, and tracking of geospatial, map and location data and information; software as a service (SaaS) featuring software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; software as a service (SaaS) featuring software for artificial intelligence, machine learning, deep learning, natural language generation, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics, business intelligence, and computer vision; software as a service (SaaS) featuring knowledge-based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics and business intelligence; software as a service (SaaS) featuring simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; software as a service (SaaS) featuring software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, hosting, security, and tracking of data and information; software as a service (SaaS) featuring software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, hosting, security, and tracking of geospatial, map and location data and information; software as a service (SaaS) featuring operating system software; software as a service (SaaS) featuring software using artificial intelligence to empower integration of data, operations and decision-making; advanced product research in the field of artificial intelligence; scientific and technological research and analysis in the field of national security; scientific and technological research and development in the field of national security; technology consultation and research in the field of national security; advance product research in the field of national security; engineering and design in the field of national security; software design and development in the field of national security; providing non-downloadable software for use in scientific and technological research and analysis in the field of national security; providing non-downloadable software for use in scientific and technological research and development in the field of national security; providing non-downloadable software for use in technology consultation and research in the field of national security; providing non-downloadable software for use in advance product research in the field of national security; providing non-downloadable software for use in engineering and design in the field of national security
Systems, techniques, and user interfaces are disclosed for an object-centric builder software that can utilize an ontology to design, configure, and build a workflow application that also references the ontology to perform a workflow. The ontology may serve as a data model for stored data associated with the particular workflow. The builder software may leverage the ontology to obtain advance knowledge of the availability and structure of the stored data that will be accessible to the workflow application at run-time, in order to build a workflow application that is well-tailored for that particular workflow. This approach may also result in flexible workflow applications that are easily built and maintained.
Computing systems methods, and non-transitory storage media are provided for obtaining images, extracting layers from each of the images, extracting segments from each of the layers, generating a compressed version of the segments by storing a single copy of each segment and metadata to reconstruct the layers from the segments and the images from the layers, and simulating a reconstruction of the image from the compressed version.
G06F 16/11 - File system administration, e.g. details of archiving or snapshots
G06F 16/174 - Redundancy elimination performed by the file system
G06F 21/64 - Protecting data integrity, e.g. using checksums, certificates or signatures
79.
SYSTEMS AND METHODS FOR GENERATING AND DISPLAYING A DATA PIPELINE USING A NATURAL LANGUAGE QUERY, AND DESCRIBING A DATA PIPELINE USING NATURAL LANGUAGE
System and method for generating and displaying data pipelines according to certain embodiments. For example, a method includes: receiving a natural language (NL) query; receiving a model result generated based on the NL query, the model result including a query in a standard query language, the model result being generated using one or more computing models; and generating the data pipeline based at least in part on the query in the standard query language, the data pipeline comprising one or more data pipeline elements, at least one data pipeline element of the one or more pipeline elements being corresponding to a query component of the query in the standard query language.
Systems and methods are provided for enhanced machine learning refinement and alert generation. An example method includes accessing datasets storing customer information reflecting transactions of customers. Individual risk scores are generated for the customers based on the customer information. Generating the risk score includes providing identified occurrences of scenario definitions and customer information as input to one or more machine learning models, the scenario definitions identifying occurrences of specific information reflected in the datasets, with the machine learning models assign respective risk scores to the customers. An interactive user interface is presented. The interactive user presents summary information associated with the risk scores, with the interactive user interfaces enabling an investigation into whether a particular customer is exhibiting risky behavior, responds to user input indicating feedback usable to update the one or more machine learning models or scenario definitions, with the feedback triggering updating of the machine learning models.
A system may receive a first user input requesting to provide an evaluator agent configuration for an evaluator agent. A system may receive a second user input specifying information associated with an agent to be evaluated. A system may receive a third user input specifying an evaluation tool, wherein the evaluation tool is configurable to evaluate the information associated with the agent. A system may receive a fourth user input specifying an evaluation tool configuration associated with the evaluation tool. A system may create the evaluator agent based on the evaluator agent configuration, wherein the evaluator agent configuration comprises an indication of the information associated with the agent to be evaluated, an indication of the evaluation tool, and an indication of the evaluation tool configuration. A system may include evaluating, using the evaluator agent, the information associated with the agent.
A method of providing ingress control comprises managing one or more replicas of an application on a software platform; creating an annotation resource that includes one or more annotations for the software platform; creating an ingress resource for a specific annotation of the one or more annotations, the specific annotation being in a specification for the application; receiving a request to access the application from a device external to the software platform, the request matching the specific annotation; and routing the request to a replica of the one or more replicas based on the ingress resource.
System and method for terminating instances and autoscaling instance groups of computing platforms. For example, a method includes determining whether an instance of an instance group is identified as eligible for termination. The method further includes, in response to determining that the instance of the instance group is identified as eligible for termination, terminating the eligible instance. The terminating the eligible instance includes, in response to a runtime of the eligible instance being equal to or larger than a predetermined maximum lifetime, terminating the eligible instance. The terminating the eligible instance further includes, in response to the runtime being smaller than the predetermined maximum lifetime, detaching the eligible instance from the instance group to allow a new instance to be associated with the instance group, and in response to the eligible instance being detached from the instance group: waiting for the new instance to be associated with the instance group, and evicting each pod associated with the detached instance. The method is performed using one or more processors.
Systems and methods for implementing sequenced filter templates to intelligently reduce a dataset to find useful patterns and source data are disclosed. An expert investigative user may configure a filter template comprising a series of filters organized in a sequence desired by the expert user. The filter template can be customized by an end user to reduce a dataset and perform guide investigation of the reduced dataset.
Example embodiments described herein pertain to a geographic information system (GIS), configured to obtain geospatial data representing a geographic area, assign a projection and coordinate system to the geospatial data, apply a transformation to the geospatial data, and generate a tile cache based on the transformed geospatial data, the tile cache including the determined projection and coordinate system.
Disclosed herein are systems and techniques for centralized data retention and deletion. Data can be ingested from multiple external data sources and saved internally for use to process data modification (e.g., deletion) requests via a data processing pipeline, which may apply eligibility checks and modification logic to determine the appropriate modifications to the relevant data items to comply with the data modification request. Various user interfaces may be generated to provide a user with oversight of the data processing pipeline and the data modifications. The user may review and trigger the modification of data stored at the external data sources and/or internally.
A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.
Systems and methods are provided for enhanced processing of time series data via parallelization of instructions. An example method includes receiving a query indicating time series datasets and operations to be performed on the time series datasets. Nodes associated with the query are identified, with each node associated with a time series dataset. Nodes associated with operations to be performed are generated. The nodes are assembled into query tree, with parent nodes of the query tree indicating operations that are to be applied to children nodes. Instructions for processing the query tree are generated. At least a subset of the instructions is provided to one or more compute systems for processing in parallel. Results are received, and presented in a user interface.
A method comprises creating and storing a dependency graph representing at least one derived dataset and one or more raw datasets or intermediate derived datasets on which the at least one derived dataset depends; reading configuration data specifying one or more periods; detecting, at a first unscheduled time, a first update to a first dataset among the one or more raw datasets or intermediate derived datasets, the first dataset being a beginning of a series of derived datasets ending with a final dataset; initiating a first transformation of the first dataset to generate a first intermediate derived dataset; detecting, at a second unscheduled time, a second update to the first dataset; determining that a throttle condition specified in the configuration data is not met; initiating, when the final dataset is not yet built in response to the first update, a second transformation of the first dataset.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
90.
GENERALIZABLE ENTITY RESOLUTION BASED ON ONTOLOGY STRUCTURES
A system for managing entity resolution processes is disclosed. The system is programmed to determine whether incoming records correspond to known entities within an ontology framework. The system is also programmed to manage a graphical user interface that allows customizing entity resolution operations and providing feedback on the determination results. The system is further programmed to use the provided feedback to improve machine learning for the entity resolution processes.
An asset owner may be interested in determining risks associated with physical assets, such as to damage or other loss associated with the assets. Accurately identifying such risks may be useful in determining preventative actions that may be taken to reduce data or loss associated with the assets. The systems and methods described herein generally relate to automating a process of obtaining data regarding physical assets, such as from sensors associated with the assets, determining one or more risk indicators associated with the assets, and initiating some actions based on the determined risk indicators.
A system for automated processing and analysis of audio files for large data sets in a cloud environment. A unified analytic environment can integrate audio machine learning models for processing and analysis with a knowledge management system, including graph presentations of tracked entities, linked to audio files and/or associated translations and transcripts. Entities within such data can be searched or filtered and proposed for tracking, or identified as tracked objects. These features can allow triage and prioritization of audio files for analysis. User interfaces can facilitate feedback on transcription and translation outputs, thereby improving present outputs and future inputs and outputs. Entities speaking or referred to can be found, tagged, and distinguished in audio files (e.g., using speaker identification in audio files, text searching in transcripts, etc.) Users can provide feedback and input on various aspects of a system, to enhance or adjust initial automated or other machine learning outputs.
A resource dependency system displays two dynamically interactive interfaces in a resource dependency user interface, a hierarchical resource repository and a dependency graph user interface. User interactions on each interface can dynamically update either interface. For example, a selection of a particular resource in the dependency graph user interface causes the system to update the dependency graph user interface to indicate the selection and also updates the hierarchical resource repository to navigate to the appropriate folder corresponding to the stored location of the selected resource. In another example, a selection of a particular resource in the hierarchical resource repository causes the system to update the hierarchical resource repository to indicate the selection and also updates the dependency graph user interface to display an updated graph, indicate the selection and, in some embodiments, focus on the selected resource by zooming into a portion of the graph.
A method of managing decoupled front-end and back-end processes is disclosed. The method comprises receiving a first result of user interaction with a first front-end interface; determining that the first result represents a validation of a data item entered via the first front-end interface; mapping the data item in a validated form to a back-end object; causing storing the data item in a database system in association with the back-end object; receiving a second result of user interaction with a second front-end interface; determining that the second result represents a state transition corresponding to executing a query entered via the second front-end interface against the database system; mapping the state transition to a set of back-end commands; causing executing the set of back-end commands over the database system of back-end objects.
A computer system provides transaction-level data retention policy inheritance. The system may perform operations including storing a first dataset comprising a plurality of transactions, each of the plurality of transactions comprising one or more data items; receiving a first transaction to the first dataset, the first transaction comprising one or more data items; determining a first retention policy for the first transaction; and storing the first retention policy with the first transaction. The system may further perform operations including calculating a deletion date for the first transaction based on the first retention policy; and storing the deletion date with the first transaction in the first dataset.
Computer-implemented systems and methods including language models for explaining and resolving code errors. A computer-implemented method may include: receiving or accessing a log comprising an error message, the error message indicating an error in code; determining the error message from the log; determining a context associated with the error; generating a prompt for a large language model (“LLM”), the prompt comprising at least: the error message, and the context associated with the error; transmitting the prompt to the LLM; and receiving an output from the LLM in response to the prompt, the output comprising at least: an explanation of the error message, and a suggested fix for the error.
Systems are provided for managing access to a log of dataset that is generated when the dataset is accessed. A system stores, with respect to each of a log producer and a log accessor, an encrypted symmetric key for dataset that is encrypted using a corresponding public key. The system returns the encrypted symmetric key for the log producer, such that the log producer can decrypt the dataset that is encrypted using the symmetric key. A log of the dataset is generated when the log producer accesses the dataset.
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
Systems, methods, and non-transitory computer readable media are provided for using linked documents. A system may receive, from a computing device, a request for a document. Content of the document may be defined based on state information and stateless information. A system may determine a local replica of the document in a local database. The local replica of the document may be linked to a primary replica of the document. The local replica of the document may include a snapshot of the primary replica of the document. The primary replica of the document may be stored in a remote database which may be accessible through a remote server. The system may subscribe to the primary replica of the document through the remote server, and may provide access to the document to the computing device based at least in part on the subscription to the primary replica of the document.
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06F 16/11 - File system administration, e.g. details of archiving or snapshots
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
G06F 17/14 - Fourier, Walsh or analogous domain transformations
Systems and methods are provided for creating and managing a data integration workspace. The workspace may comprise one or more views of data (or datasets) stored in or accessible by the system. Models may be generated and updated based on the plurality of datasets and presented via a graphical user interface. Feedback received via a graphical user interface presenting a model may be used to annotate an underlying dataset associated with the model. Responsive to a modification of the underlying dataset or the rules for using the underlying dataset to generate the model, other related datasets and/or models may be automatically updated accordingly. Templates associated with one or more types of users may be defined. Each template may comprise one or more specific models related to a specific type of user.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06F 16/21 - Design, administration or maintenance of databases
Computing systems methods, and non-transitory storage media are provided for receiving a first representation of an unstructured data entity. The first representation includes an indication of a detection. The unstructured data entity is part of a corpus. Next, second representations of the unstructured data entity are received and resolved according to a consensus. Next, any discrepancies between the first representation and the resolved second representations are determined. The any discrepancies include any difference in an existence or an absence of the detection, in a relative position of the detection, or in a type or a classification of the detection. Next, feedback regarding the any discrepancy is received. Next, the first representation is selectively modified, or selectively prompted to be modified, based on the any discrepancy and the feedback.
