Computer implemented methods for executing a database query in a database using an electronic computing device are presented, the method including: causing the electronic computing device to provide at least one data structure including at least one object having at least two properties of different data types; identifying a property of the at least one data structure that includes the smallest unique values in terms of type of data stored in that particular property; executing the database query, including any limiting parameters, configured to retrieve only data from the property including the smallest unique values that are retrievable for a record; retrieving a predefined number of results of the executed database query; and for each set of predefined number of retrieved results, executing a new database access thread that is configured to retrieve data that are present in the records identified with the smallest unique values.
The present disclosure provides a computer-implemented method for scoring and visualizing combined search results, comprising: (a) performing a plurality of individual searches on data objects stored in a database, wherein the data objects are stored in defined fixed data structures; (b) combining the plurality of individual searches into a combined search; (c) determining a weight for each of the individual searches; and (d) obtaining a search result of the combined search, wherein the search result of the combined search comprises scores associated with a subset of the data objects.
The present disclosure provides a computer-implemented method for applying access rights to a database comprising a plurality of data units. The method may comprise receiving a request from a user to perform an operation directed to at least a subset of data objects stored in the database. Next, access rights associated with the user may be determined. The access rights may comprise an access permission to a subset of one or more of the data units that is implemented by performing a filter operation. The operation and the filter operation may then be performed concurrently to the at least subset of data objects to obtain a filtered data set.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
G06F 16/10 - Systèmes de fichiersServeurs de fichiers
G06F 16/20 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données structurées, p. ex. de données relationnelles
The present disclosure provides systems and methods for end-to-end machine learning. A method of the present disclosure may comprise one or more operations of data ingestion, data preparation, feature storage, model building, and productionizing by the model. The methods and systems of the present disclosure may use an Automated Machine Learning (AutoML) algorithm and eXplainable Artificial Intelligence (XAI).
Computer implemented methods for storing ad hoc relations between previously unrelated database objects assigned to different database structures using an electronic computing device are presented, the methods including: causing the electronic computing device to define at least three database structures: structure A, structure B and structure C, where each of the at least three database structures each includes a number of objects, where there exists at least one relation between objects of structure A and objects of structure B, and where there exists at least one relation between objects of structure B and objects of structure C; filtering data of structure A; accessing structure B using a first selected relation between structure A and structure B; storing information about filtering of structure A and information on a first selected path between structure A and structure B; filtering results obtained from structure B.
A computer-implemented method for traversing a graph comprising: generating a metadata graph by reducing the graph, wherein the metadata graph is generated based on metadata describing one or more vertices and one or more edges of the graph. The metadata graph can comprise one or more edge types and one or more reduced vertices. Edge types in the metadata graph can be filtered to optimize finding of a path between a source vertex and a target vertex within a predetermined maximum path length.
Computer implemented methods for database hierarch-independent data drilling are presented including: a. selecting one of at least two database structures each having data, where the at least two database structures include, at least two distinct paths that lead from a first of the at least two database structures to a second of the at least two database structures, where a path logically relates at least two data structures which are otherwise directly unrelated using data structures and data structures' relations, and a database information schema that provides information about the at least two database structures including information regarding relations between data structures; b. setting the selected database structure as a current data drilling state; and c. finding at least one related data structure corresponding with the selected database structure for the current data drilling state utilizing the database information schema.
The present disclosure provides a computer-implemented method for applying an analysis to a data model comprising data objects. The method may comprise receiving the analysis and the first data model each in semantic format. Next, the analysis and the data model may be computer processed to (i) identify one or more elements missing from the data model and (ii) determine that the analysis is not applicable to the data model upon identification of the one or more elements. The one or more elements may then be presented to a user for adjusting the data model. This may be repeated until the analysis is applicable to the data model. The analysis may then be performed on the data objects of the data model.
The present disclosure provides systems and methods for end-to-end machine learning. A method of the present disclosure may comprise one or more operations of data ingestion, data preparation, feature storage, model building, and productionizing by the model. The methods and systems of the present disclosure may use an Automated Machine Learning (AutoML) algorithm and eXplainable Artificial Intelligence (XAI).
The present disclosure provides a computer-implemented method for traversing a graph. The method can comprise generating a metadata graph by reducing the graph, wherein the metadata graph is generated based on metadata describing one or more vertices and one or more edges of the graph. The metadata graph can comprise one or more edge types and one or more reduced vertices. Edge types in the metadata graph can be filtered to optimize finding of a path between a source vertex and a target vertex within a predetermined maximum path length.
A computer implemented method for creating and managing a database system comprising data structures for storing, in a memory, data and relations between the data, the method comprising the steps of creating a mind map structure wherein each node of the mind map represents a set in the first data structure and each branch represents a relation in the fifth data structure of the database in which there are defined five data structures that hold all information relating to tables, records and relations, namely: a first data structure comprising a definition of at least one data set, a second data structure comprising definitions of properties of objects, a third data structure comprising definitions of objects, a fourth data structure comprising definitions of properties of each object, a fifth data structure comprising definitions of relations and a sixth data structure for storing definitions of relations between objects.
Computer implemented methods for storing ad hoc relations between previously unrelated database objects assigned to different database structures using an electronic computing device are presented, the methods including: causing the electronic computing device to define at least three database structures: structure A, structure B and structure C, where each of the at least three database structures each includes a number of objects, where there exists at least one relation between objects of structure A and objects of structure B, and where there exists at least one relation between objects of structure B and objects of structure C; filtering data of structure A; accessing structure B using a first selected relation between structure A and structure B; storing information about filtering of structure A and information on a first selected path between structure A and structure B; filtering results obtained from structure B.
A method for providing visualization of data objects in a relational database is provided. The method comprises: (a) bringing an electronic device of a user in communication with a server comprising the non-hierarchical relational database, (b) generating and displaying a graph comprising visual graphical elements including a first node representing a first class encompassing a first subset of the data objects, a second node representing a second class encompassing a second subset of the data objects, and a link representing a relationship between the first class and the second class, (c) receiving a request via the user interface of the electronic device to perform a task directed to at least a subset of the data objects, (d) generating one or more filtering operations for the task and, upon execution, producing a graphical result comprising a filtered data set, and (e) automatically displaying the graphical result on the user interface.
A computing system or a method provides a user interface to perform data analysis in a relational database, comprising: (a) bringing an electronic device of a user in communication with a computer server comprising the relational database that stores data objects in a non-hierarchical manner, which electronic device comprises a user interface; (b) receiving a request from the user via the user interface to perform a task directed to at least a subset of the data objects; (c) generating filtering operations for the task, which filtering operations is stored in a memory unit and, upon execution, generates a filtered data set from the subset of the data objects; and (d) automatically generating a search path comprising a plurality of visual graphical elements on the user interface, and the visual graphical elements correspond to the one or more filtering operations.
A computer implemented method for creating and managing a database system comprising data structures for storing, in a memory, data and relations between the data, the method comprising the steps of creating a mind map structure wherein each node of the mind map represents a set in the first data structure and each branch represents a relation in the fifth data structure of the database in which there are defined five data structures that hold all information relating to tables, records and relations, namely: a first data structure comprising a definition of at least one data set, a second data structure comprising definitions of properties of objects, a third data structure comprising definitions of objects, a fourth data structure comprising definitions of properties of each object, a fifth data structure comprising definitions of relations and a sixth data structure for storing definitions of relations between objects.
The present disclosure provides a computer-implemented method for applying access rights to a database comprising a plurality of data units. The method may comprise receiving a request from a user to perform an operation directed to at least a subset of data objects stored in the database. Next, access rights associated with the user may be determined. The access rights may comprise an access permission to a subset of one or more of the data units that is implemented by performing a filter operation. The operation and the filter operation may then be performed concurrently to the at least subset of data objects to obtain a filtered data set.
G06F 16/10 - Systèmes de fichiersServeurs de fichiers
G06F 16/20 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données structurées, p. ex. de données relationnelles
The present disclosure provides a computer-implemented method for applying an analysis to a data model comprising data objects. The method may comprise receiving the analysis and the first data model each in semantic format. Next, the analysis and the data model may be computer processed to (i) identify one or more elements missing from the data model and (ii) determine that the analysis is not applicable to the data model upon identification of the one or more elements. The one or more elements may then be presented to a user for adjusting the data model. This may be repeated until the analysis is applicable to the data model. The analysis may then be performed on the data objects of the data model.
The present disclosure provides a computer-implemented method for scoring and visualizing combined search results, comprising: (a) performing a plurality of individual searches on data objects stored in a database, wherein the data objects are stored in defined fixed data structures; (b) combining the plurality of individual searches into a combined search; (c) determining a weight for each of the individual searches; and (d) obtaining a search result of the combined search, wherein the search result of the combined search comprises scores associated with a subset of the data objects.
Computer implemented methods for database hierarchy-independent data drilling are presented including: a. selecting one of at least two database structures each having data, where the at least two database structures include, at least two distinct paths that lead from a first of the at least two database structures to a second of the at least two database structures, where a path logically relates at least two data structures which are otherwise directly unrelated using data structures and data structures' relations, and a database information schema that provides information about the at least two database structures including information regarding relations between data structures; b. setting the selected database structure as a current data drilling state; and c. finding at least one related data structure corresponding with the selected database structure for the current data drilling state utilizing the database information schema.
The present disclosure provides a computer-implemented method for scoring and visualizing combined search results, comprising: (a) performing a plurality of individual searches on data objects stored in a database, wherein the data objects are stored in defined fixed data structures; (b) combining the plurality of individual searches into a combined search; (c) determining a weight for each of the individual searches; and (d) obtaining a search result of the combined search, wherein the search result of the combined search comprises scores associated with a subset of the data objects.
The present disclosure provides a computer-implemented method for applying access rights to a database comprising a plurality of data units. The method may comprise receiving a request from a user to perform an operation directed to at least a subset of data objects stored in the database. Next, access rights associated with the user may be determined. The access rights may comprise an access permission to a subset of one or more of the data units that is implemented by performing a filter operation. The operation and the filter operation may then be performed concurrently to the at least subset of data objects to obtain a filtered data set.
The present disclosure provides a computer-implemented method for applying an analysis to a data model comprising data objects. The method may comprise receiving the analysis and the first data model each in semantic format. Next, the analysis and the data model may be computer processed to (i) identify one or more elements missing from the data model and (ii) determine that the analysis is not applicable to the data model upon identification of the one or more elements. The one or more elements may then be presented to a user for adjusting the data model. This may be repeated until the analysis is applicable to the data model. The analysis may then be performed on the data objects of the data model.
A computing system or a method provides a user interface to perform data analysis in a relational database, comprising: (a) bringing an electronic device of a user in communication with a computer server comprising the relational database that stores data objects in a non-hierarchical manner, which electronic device comprises a user interface; (b) receiving a request from the user via the user interface to perform a task directed to at least a subset of the data objects; (c) generating filtering operations for the task, which filtering operations is stored in a memory unit and, upon execution, generates a filtered data set from the subset of the data objects; and (d) automatically generating a search path comprising a plurality of visual graphical elements on the user interface, and the visual graphical elements correspond to the one or more filtering operations.
A method for providing visualization of data objects in a relational database is provided. The method comprises: (a) bringing an electronic device of a user in communication with a server comprising the non-hierarchical relational database, (b) generating and displaying a graph comprising visual graphical elements including a first node representing a first class encompassing a first subset of the data objects, a second node representing a second class encompassing a second subset of the data objects, and a link representing a relationship between the first class and the second class, (c) receiving a request via the user interface of the electronic device to perform a task directed to at least a subset of the data objects, (d) generating one or more filtering operations for the task and, upon execution, producing a graphical result comprising a filtered data set, and (e) automatically displaying the graphical result on the user interface.
Computer implemented methods for executing a database query in a database using an electronic computing device are presented, the method including: causing the electronic computing device to provide at least one data structure including at least one object having at least two properties of different data types; identifying a property of the at least one data structure that includes the smallest unique values in terms of type of data stored in that particular property; executing the database query, including any limiting parameters, configured to retrieve only data from the property including the smallest unique values that arc retrievable for a record; retrieving a predefined number of results of the executed database query; and for each set of predefined number of retrieved results, executing a new database access thread that is configured to retrieve data that are present in the records identified with the smallest unique values.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Electronic database in the field of data storage and analysis recorded on computer media; Interactive database management software for general use by businesses; Enterprise software in the nature of a database for non-transactional data and a search engine for database content; Downloadable software for business data analysis in the fields of government, financial services, insurance; Computer software for use in content management; Computer software packages for data analysis in the fields of fraud, crime, intelligence, and anti-money laundering Business management and administrative services; Business data analysis and consultation services Information technology consulting services; Software development, programming and implementation; Software as a service (SAAS) services featuring software for data analysis in the fields of fraud, crime, intelligence, and anti-money laundering; Rental of computer software; Platform as a service (PAAS) featuring computer software platforms for data analysis in the fields of fraud, crime, intelligence, and anti-money laundering; Providing temporary use of non-downloadable software to analyze financial data and generate reports
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Recorded content; Software; Databases (electronic); Interactive databases; Enterprise software; Software for the analysis of business data; Content management software; Computer software packages. Business assistance, management and administrative services; Business data analysis services; Advisory services relating to business analysis. IT services; Software development, programming and implementation; Hosting services and software as a service and rental of software; Platform as a service [PaaS]; Providing temporary use of non-downloadable software for analyzing financial data and generating reports.
28.
Computer-implemented method for storing unlimited amount of data as a mind map in relational database systems
A computer implemented method for creating and managing a database system comprising data structures for storing, in a memory, data and relations between the data, the method comprising the steps of creating a mind map structure wherein each node of the mind map represents a set in the first data structure and each branch represents a relation in the fifth data structure of the database in which there are defined five data structures that hold all information relating to tables, records and relations, namely: a first data structure comprising a definition of at least one data set, a second data structure comprising definitions of properties of objects, a third data structure comprising definitions of objects, a fourth data structure comprising definitions of properties of each object, a fifth data structure comprising definitions of relations and a sixth data structure for storing definitions of relations between objects.
Computer implemented methods for storing ad hoc relations between previously unrelated database objects assigned to different database structures using an electronic computing device are presented, the methods including: causing the electronic computing device to define at least three database structures: structure A, structure B and structure C, where each of the at least three database structures each includes a number of objects, where there exists at least one relation between objects of structure A and objects of structure B, and where there exists at least one relation between objects of structure B and objects of structure C; filtering data of structure A; accessing structure B using a first selected relation between structure A and structure B; storing information about filtering of structure A and information on a first selected path between structure A and structure B; filtering results obtained from structure B.
Computer implemented methods for storing ad hoc relations between previously unrelated database objects assigned to different database structures using an electronic computing device are presented, the methods including: causing the electronic computing device to define at least three database structures: structure A, structure B and structure C, where each of the at least three database structures each includes a number of objects, where there exists at least one relation between objects of structure A and objects of structure B, and where there exists at least one relation between objects of structure B and objects of structure C; filtering data of structure A; accessing structure B using a first selected relation between structure A and structure B; storing information about filtering of structure A and information on a first selected path between structure A and structure B; filtering results obtained from structure B.
Computer implemented methods for database hierarchy-independent data drilling are presented including: a. selecting one of at least two database structures each having data, where the at least two database structures include, at least two distinct paths that lead from a first of the at least two database structures to a second of the at least two database structures, where a path logically relates at least two data structures which are otherwise directly unrelated using data structures and data structures' relations, and a database information schema that provides information about the at least two database structures including information regarding relations between data structures; b. setting the selected database structure as a current data drilling state; and c. finding at least one related data structure corresponding with the selected database structure for the current data drilling state utilizing the database information schema.
A computer implemented method for creating and managing a database system comprising data structures for storing, in a memory, data and relations between the data, the method comprising the steps of creating a mind map structure wherein each node of the mind map represents a set in the first data structure and each branch represents a relation in the fifth data structure of the database in which there are defined five data structures that hold all information relating to tables, records and relations, namely: a first data structure comprising a definition of at least one data set, a second data structure comprising definitions of properties of objects, a third data structure comprising definitions of objects, a fourth data structure comprising definitions of properties of each object, a fifth data structure comprising definitions of relations and a sixth data structure for storing definitions of relations between objects.
