According to one aspect of the present invention there is provided a system, method, and computer program product for recovering from a network failure in a communication network using network function virtualization (NFV-based network), the method including: selecting a first network component of the NFV-based network, detecting at least one probable failure of the first network component, selecting a second network component to be used for replacing the instance of the VNF in the first network component prior to a failure of the first network component, and securing at least one resource of the selected second network component for the other instance of the VNF and maintaining, in the selected second network component, an updated copy of data associated with the instance of the VNF in the first network component.
H04L 41/40 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant la virtualisation des fonctions réseau ou ressources, p. ex. entités SDN ou NFV
H04L 41/0659 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant la reprise sur incident de réseau en isolant ou en reconfigurant les entités défectueuses
2.
System, method, and computer program for orchestrating time-limited AI-inferencing
As described herein, a system, method, and computer program are provided for processing a dataset. In one embodiment, an AI-model to inference the dataset is selected. A plurality of inferencing engines each using the AI-model are initiated, where a number of the inferencing engines that are initiated is calculated according to a predetermined time constraint. The dataset is divided between the plurality of inferencing engines.
G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
As described herein, a system, method, and computer program provide explainability of entity data segmentation based on Boolean friction points. A dataset is processed, using a machine learning model, to calculate a plurality of Shapley values for the dataset, wherein the dataset includes friction points and explanatory variables. The dataset is clustered to generate a plurality of segments, based on the Shapley values. For each segment of the plurality of segments, a global explanation is generated for the segment using a predefined list of Boolean friction columns and the Shapley values.
As described herein, a system, method, and computer program are provided for code customization. A customization of existing code or metadata defining a software application is received, to form a customized version of the software application. The customization is tagged with a label that differentiates the customization from the existing code or metadata. During runtime or compilation time, a conditional logical selection between the existing code or metadata and the customization is made, using the label.
As described herein, a system, method, and computer program are provided for scraping POM data from webpages. A plug-in tool of a web browser receives input defining one or more parameters for extracting page object model (POM) data from a webpage. The plug-in tool automatically extracts the POM data from the webpage based on the one or more parameters defined in the input.
As described herein, a system, method, and computer program are provided for selectively amending a large customer agreement. A written contract for a customer representing an agreement to provision a plurality of telecommunication services at a plurality of sites of the customer is accessed. A user interface is provided presenting, as a plurality of selectable elements, a plurality of items in the written contract. An update to the written contract is received via the user interface. The update is processed as a selective amendment to the written contract to form an amended version of the written contract.
G06Q 30/016 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance après-vente
7.
SYSTEM, METHOD, AND COMPUTER PROGRAM FOR EVOLVING MULTI-TURN CHATBOT DIALOGS
As described herein, an LLM-based chatbot is evolved over at least one iteration. The iteration includes presenting, by a LLM-based evaluator, a question to a LLM-based chatbot during a dialog with the LLM-based chatbot comprised of a sequence of question and answer pairs. The iteration includes receiving, by the LLM- based evaluator, an answer to the question from the LLM-based chatbot. The iteration includes evaluating, by the LLM-based evaluator, the answer according to one or more evaluation metrics and a ground truth. The iteration includes determining, by the LLM-based evaluator, that a result of the evaluation is unsatisfactory. The iteration includes presenting, by the LLM-based evaluator, a follow-up question to the LLM-based chatbot designed to encourage a new answer of the LLM-based chatbot to be satisfactory with respect to the ground truth and to cause an optimization of the LLM-based chatbot.
As described herein, an LLM-based chatbot is evolved over at least one iteration. The iteration includes presenting, by a LLM-based evaluator, a question to a LLM-based chatbot during a dialog with the LLM-based chatbot comprised of a sequence of question and answer pairs. The iteration includes receiving, by the LLM-based evaluator, an answer to the question from the LLM-based chatbot. The iteration includes evaluating, by the LLM-based evaluator, the answer according to one or more evaluation metrics and a ground truth. The iteration includes determining, by the LLM-based evaluator, that a result of the evaluation is unsatisfactory. The iteration includes presenting, by the LLM-based evaluator, a follow-up question to the LLM-based chatbot designed to encourage a new answer of the LLM-based chatbot to be satisfactory with respect to the ground truth and to cause an optimization of the LLM-based chatbot.
As described herein, a system, method, and computer program are provided for optimization of allocation of compute job resources in a multi-cloud environment. A compute job to be run is identified. An optimization target for the compute job is determined. Resource requirements of the compute job and resource availability for a plurality of cloud networks are processed to determine a resource allocation across the plurality of cloud networks that satisfies the optimization target for the compute job. The resource allocation is orchestrated for the compute job.
As described herein, a system, method, and computer program are provided for optimization of allocation of compute job resources in a multi-cloud environment. A compute job to be run is identified. An optimization target for the compute job is determined. Resource requirements of the compute job and resource availability for a plurality of cloud networks are processed to determine a resource allocation across the plurality of cloud networks that satisfies the optimization target for the compute job. The resource allocation is orchestrated for the compute job.
As described herein, a system, method, and computer program are provided for transferring a user subscription between mobile devices of different OEMs. A request to transfer a subscription to a carrier service of a service provider from a first mobile device having a first operating system to a second mobile device having a second operating system is received. A flow for transferring the subscription from the first mobile device having the first operating system to the second mobile device having the second operating system is performed.
H04W 8/20 - Transfert de données utilisateur ou abonné
H04W 8/18 - Traitement de données utilisateur ou abonné, p. ex. services faisant l'objet d'un abonnement, préférences utilisateur ou profils utilisateurTransfert de données utilisateur ou abonné
12.
SYSTEM, METHOD, AND COMPUTER PROGRAM FOR INTENT-BASED COMMUNICATION SERVICE ORCHESTRATION WITH GENERATIVE AI ASSISTANCE
As described herein, a system, method, and computer program are provided for intent-based communication service orchestration with generative AI assistance. An intent describing properties of a required service is processed, using a large language model (LLM), to translate the intent into a communication service capable of being orchestrated in a network. The communication service is orchestrated in the network.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
H04L 41/5041 - Gestion des services réseau, p. ex. en assurant une bonne réalisation du service conformément aux accords caractérisée par la relation temporelle entre la création et le déploiement d’un service
13.
System, method, and computer program for orchestrating time-limited AI-inferencing
As described herein, a system, method, and computer program are provided for processing a dataset. In one embodiment, an AI-model to inference the dataset is selected. A plurality of inferencing engines each using the AI-model are initiated, where a number of the inferencing engines that are initiated is calculated according to a predetermined time constraint. The dataset is divided between the plurality of inferencing engines.
G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
As described herein, a system, method, and computer program are provided for transferring a user subscription between mobile devices of different OEMs. A request to transfer a subscription to a carrier service of a service provider from a first mobile device having a first operating system to a second mobile device having a second operating system is received. A flow for transferring the subscription from the first mobile device having the first operating system to the second mobile device having the second operating system is performed.
As described herein, a system, method, and computer program are provided for intent-based communication service orchestration with generative AI assistance. An intent describing properties of a required service is processed, using a large language model (LLM), to translate the intent into a communication service capable of being orchestrated in a network. The communication service is orchestrated in the network.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
H04L 41/5003 - Gestion des accords de niveau de service [SLA]Interaction entre l'accord de niveau de service et la qualité de service [QoS]
16.
System, method, and computer program for direct API call authentication during an end-to-end test flow
As described herein, a system, method, and computer program are provided for direct API call authentication during an end-to-end test flow. During use of an end-to-end testing framework, a network log is stored that includes an authentication token issued by an identity provider. The authentication token is then used for making a direct API call during a test flow of the end-to-end testing framework.
As described herein, a system, method, and computer program are provided for batching a collection of elements in local memory for processing. A single collection of elements of data is stored in a local memory across a plurality of sub-collections. The single collection of elements is processed on a sub-collection basis, where each sub-collection is removed from the local memory upon completion of the processing of the elements in the sub-collection.
As described herein, a system, method, and computer program are provided for batching a collection of elements in local memory for processing. A single collection of elements of data is stored in a local memory across a plurality of sub-collections. The single collection of elements is processed on a sub-collection basis, where each sub-collection is removed from the local memory upon completion of the processing of the elements in the sub-collection.
As described herein, a system, method, and computer program are provided for leveraging network state information when exposing network capabilities. A request for one or more capabilities of a network is received from an application by a platform that interfaces the network. The platform communicates with an active inventory of the network for handling the request.
H04L 41/0853 - Récupération de la configuration du réseauSuivi de l’historique de configuration du réseau en recueillant activement des informations de configuration ou en sauvegardant les informations de configuration
H04L 41/12 - Découverte ou gestion des topologies de réseau
H04L 41/0806 - Réglages de configuration pour la configuration initiale ou l’approvisionnement, p. ex. prêt à l’emploi [plug-and-play]
H04L 41/0895 - Configuration de réseaux ou d’éléments virtualisés, p. ex. fonction réseau virtualisée ou des éléments du protocole OpenFlow
H04L 41/40 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant la virtualisation des fonctions réseau ou ressources, p. ex. entités SDN ou NFV
20.
SYSTEM, METHOD, AND COMPUTER PROGRAM FOR LEVERAGING NETWORK STATE INFORMATION WHEN EXPOSING CORE NETWORK CAPABILITIES
As described herein, a system, method, and computer program are provided for leveraging network state information when exposing network capabilities. A request for one or more capabilities of a network is received from an application by a platform that interfaces the network. The platform communicates with an active inventory of the network for handling the request.
As described herein, a system, method, and computer program are provided for securing a network whose capabilities are accessible by external applications via an API. A request for one or more capabilities of a network is received from an application by an API Gateway of a platform that interfaces the network. Information associated with the request is input to a machine learning model to cause the machine learning model to predict whether the request is at least potentially malicious. The request is prevented from being sent to the network when the machine learning model predicts that the request is at least potentially malicious. The request is sent to the network when the machine learning model predicts that the request is not at least potentially malicious.
As described herein, a system, method, and computer program are provided for securing a network whose capabilities are accessible by external applications via an API. A request for one or more capabilities of a network is received from an application by an API Gateway of a platform that interfaces the network. Information associated with the request is input to a machine learning model to cause the machine learning model to predict whether the request is at least potentially malicious. The request is prevented from being sent to the network when the machine learning model predicts that the request is at least potentially malicious. The request is sent to the network when the machine learning model predicts that the request is not at least potentially malicious.
As described herein, a system, method, and computer program are provided for autoscaling data lake connections. One or more metrics defining a load on one or more data sources included in a data lake are collected. A plurality of processes configured to connect to the data lake to retrieve data therefrom are automatically scaled, as a function of the one or more metrics.
As described herein, a system, method, and computer program are provided for managing quality of 5G network slice services. A latency issue in a 5G network is detected. Information associated with the 5G network is collected. The information is analyzed to determine a network slice provisioned in the 5G network having a quality requirement that is not met as a result of the latency issue. The network slice is reengineered, using the information associated with the 5G network. The reengineered network slice is deployed in the 5G network.
As described herein, a system, method, and computer program provide explainability of entity data segmentation based on Boolean friction points. A dataset is processed, using a machine learning model, to calculate a plurality of Shapley values for the dataset, wherein the dataset includes friction points and explanatory variables. The dataset is clustered to generate a plurality of segments, based on the Shapley values. For each segment of the plurality of segments, a global explanation is generated for the segment using a predefined list of Boolean friction columns and the Shapley values.
SYSTEM, METHOD, AND COMPUTER PROGRAM FOR USING A GENERATIVE MODEL TO PROVIDE SEAMLESS ADAPTATION OF CONTENT TO THE REQUIREMENTS OF AN AREA OF JURISDICTION
As described herein, a system, method, and computer program are provided for using a generative model to adapt a content. The content and an indication of one or more content requirements are processed to determine one or more elements of the content that are not in compliance with the content requirements. A generative model is used to adapt the one or more elements of the content to the one or more content requirements. The content having the one or more adapted elements is output.
SYSTEM, METHOD, AND COMPUTER PROGRAM FOR USING A GENERATIVE MODEL TO PROVIDE SEAMLESS ADAPTATION OF CONTENT TO THE REQUIREMENTS OF AN AREA OF JURISDICTION
As described herein, a system, method, and computer program are provided for using a generative model to adapt a content. The content and an indication of one or more content requirements are processed to determine one or more elements of the content that are not in compliance with the content requirements. A generative model is used to adapt the one or more elements of the content to the one or more content requirements. The content having the one or more adapted elements is output.
As described herein, a system, method, and computer program are provided for multi-channel application testing using generative AI. A test automation flow generated for an application is accessed. Generative artificial intelligence (AI) is used to automatically adapt the test automation flow to a plurality of versions of the application corresponding to different channels. The plurality of versions of the application are tested using the adapted test automation flows.
As described herein, a system, method, and computer program are provided for multi-channel application testing using generative AI. A test automation flow generated for an application is accessed. Generative artificial intelligence (AI) is used to automatically adapt the test automation flow to a plurality of versions of the application corresponding to different channels. The plurality of versions of the application are tested using the adapted test automation flows.
As described herein, a system, method, and computer program are provided for unifying deployment of microservices. A plurality of microservices to be deployed to a system are determined. Deployments of the plurality of microservices are unified into a single deployment of the plurality of microservices to the system.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
H04L 67/00 - Dispositions ou protocoles de réseau pour la prise en charge de services ou d'applications réseau
31.
System, method, and computer program for data validation during transfer of data from source to target
As described herein, a system, method, and computer program are provided for data validation during transfer of data from source to target. A transfer of data from a source to a target is detected. The data transferred from the source is compared to data at the target resulting from the transfer. The transfer is validated based on a result of the comparison. A result of the validation is output.
G06F 16/21 - Conception, administration ou maintenance des bases de données
G06F 11/10 - Détection ou correction d'erreur par introduction de redondance dans la représentation des données, p. ex. en utilisant des codes de contrôle en ajoutant des chiffres binaires ou des symboles particuliers aux données exprimées suivant un code, p. ex. contrôle de parité, exclusion des 9 ou des 11
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
32.
SYSTEM, METHOD, AND COMPUTER PROGRAM FOR UNIFIED DEPLOYMENT OF MICROSEVICES
As described herein, a system, method, and computer program are provided for unifying deployment of microservices. A plurality of microservices to be deployed to a system are determined. Deployments of the plurality of microservices are unified into a single deployment of the plurality of microservices to the system.
As described herein, a system, method, and computer program are provided for using a dynamic threshold mechanism that is utilizing a set of machine learning models to auto-complete user input fields. User access to a form having a plurality of user input fields is detected. One or more of the plurality of user input fields are auto-completed over a sequence of stages, utilizing at least one machine learning model.
As described herein, a system, method, and computer program are provided for using a dynamic threshold mechanism that is utilizing a set of machine learning models to auto-complete user input fields. User access to a form having a plurality of user input fields is detected. One or more of the plurality of user input fields are auto-completed over a sequence of stages, utilizing at least one machine learning model.
As described herein, a system, method, and computer program are provided for providing shard-aware bulk requests for a Cassandra No-SQL database system having a plurality of distributed nodes with replication. A request to perform a database operation on the Cassandra No-SQL database system is received from an application. Token ranges of partition keys included with the request are determined. The request is grouped with a plurality of additional database operation requests to form a bulk request, where requests are grouped by a target node in the Cassandra No-SQL database system such that the target node holds token ranges for all requests included in the bulk request. The bulk request is communicated to the target node of the Cassandra No-SQL database system for processing of the requests included in the bulk request.
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
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
36.
System, method, and computer program for automated generation of feed loader applications
As described herein, a system, method, and computer program are provided for automatic generation of feed loader applications. An input defining configuration details for a target repository is received. The input is used to automatically generate an application configured to load data to the target repository. The application is deployed for use in loading data in one or more given data files to the target repository.
As described herein, a system, method, and computer program are provided for creating a new class of instances. A first dataset comprising a plurality of instances is obtained. A first AI engine is used to classify the plurality of instances into a plurality of classes. Each class of instances of the first dataset is associated with a respective action having a positive result or a lack of the positive result. A class is selected and the respective action is executed on instances of the class. Instances of the selected class for which the respective action resulted in a lack of the positive result are collected. The collection of instances are used to train an AI-model, and/or a second AI engine is used to classify the collection of instances, and/or a plurality of artificial instances are synthesized based on the collection of instances.
A system, method, and computer program are provided for unattended test execution based on impacted application code. A change made to an application is detected. One or more features of the application impacted by the change made to the application are determined. A plurality of existing tests associated with the one or more features of the application impacted by the change made to the application are identified. A probability of each existing test in the plurality of existing tests exposing a defect in the application is predicted. At least a portion of the plurality of existing tests are executed for the application in an order that based on the predicted probabilities.
As described herein, a system, method, and computer program are provided for intent translation to Topology and Orchestration Specification for Cloud Applications (TOSCA) in intent-based orchestration. A microservice of a service and network orchestrator receives an intent defined in a first format associated with a first standard used for modeling and management of network services. The microservice translates the intent defined in the first format to a second format associated with a TOSCA-based model used for modeling and management of network services, to form the intent defined in the second format. The microservice outputs the intent defined in the second format.
As described herein, a system, method, and computer program provide automatic content merging for an optimistic concurrency control mechanism. A concurrency error resulting from a first source requesting a first update to a resource concurrently with a second source requesting a second update to the resource is detected. Responsive to detecting the concurrency error, the first update and the second update are merged to form a merged update. The merged update is saved to the resource.
As described herein, a system, method, and computer program are provided for orchestrating asynchronous processes to prevent data corruption. An orchestrator identifies a first asynchronous process executing in a computer system, wherein the first asynchronous process is configured to update data. The orchestrator detects activation of a second asynchronous process in the computer system which is configured to update the data. The orchestrator prevents the second asynchronous process from executing in the computer system to update the data at least while the first asynchronous process is executing in the computer system, to avoid simultaneous updates to the data by the first asynchronous process and the second asynchronous process.
As described herein, a system, method, and computer program are provided for an exactly once messaging protocol in a publish-subscribe messaging system. A consumer (i.e. subscriber) of a publish-subscribe messaging system is identified. For each required consumer, and for each subscribed topic of the consumer, a new dedicated consumer is created for the topic in the publish-subscribe messaging system. The new dedicated consumer is used to ensure that messages published to the topic are delivered exactly once to each associated consumer.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p. ex. pour le traitement simultané de plusieurs programmes
H04L 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation
As described herein, a system, method, and computer program are provided for making a 5G private network deployment recommendation using machine learning. A plurality of parameter values associated with an enterprise for which a 5G private network is to be deployed are obtained. A machine learning model is used to infer, for the enterprise, an optimal deployment scenario for the 5G private network among a plurality of available deployment scenarios, based on the plurality of parameter values. An indication of the optimal deployment scenario is output as a recommendation for deploying the for the 5G private network for the enterprise.
As described herein, a system, method, and computer program are provided for providing automated management of electronic device inventory. An electronic device is triggered to emit at least one signal capable of being sensed by at least one sensor. The at least one signal emitted by the electronic device is sensed, using the at least one sensor. A physical location of the electronic device is determined, based on the sensed at least one signal. A discrepancy between the physical location of the electronic device and a specified location of the electronic device recorded in an inventory management system is detected. At least one action is performed to handle the discrepancy.
H04W 4/02 - Services utilisant des informations de localisation
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
H04W 4/38 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour la collecte d’informations de capteurs
H04W 4/80 - Services utilisant la communication de courte portée, p. ex. la communication en champ proche, l'identification par radiofréquence ou la communication à faible consommation d’énergie
45.
System, method, and computer program for an unattended trap for a network brute force attack
As described herein, a system, method, and computer program are provided for an unattended trap for a brute force attack. A brute force attack on private data in a computer network is detected. Secret information expected by the brute force attack is generated. At least one honeypot having the secret information is created in the computer network. A state of the at least one honeypot is updated based on simulated activity.
As described herein, a system, method, and computer program are provided for intent to service mappings in intent-based orchestration. An intent orchestrator receives an intent specifying one or more parameters of a service required for a network. The intent orchestrator translates the intent to one or more basic data types of a plurality of predefined basic data types based on the one or more parameters. The intent orchestrator forms one or more abstract services using the one or more basic data types. The intent orchestrator determines one or more specific services of a network orchestrator that correlate with the one or more abstract services. The intent orchestrator causes the network orchestrator to fulfill the intent using the one or more specific services.
H04L 67/61 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en tenant compte de la qualité de service [QoS] ou des exigences de priorité
H04L 67/568 - Stockage temporaire des données à un stade intermédiaire, p. ex. par mise en antémémoire
47.
System, method, and computer program for transferring subscriber identity module (SIM) information for SIM card or eSIM activation
A system, method, and computer program are provided for activating an eSIM from a SIM card or another eSIM. In one implementation, a request to activate an eSIM from a SIM card or another eSIM is received. Additionally, responsive to the request, first information associated with the SIM card or the other eSIM and second information associated with the eSIM is accessed. Further, at least one action to activate the eSIM from the SIM card or the other eSIM is caused to be performed, where the at least one action is based on the first information and the second information.
H04W 4/50 - Fourniture de services ou reconfiguration de services
H04W 8/18 - Traitement de données utilisateur ou abonné, p. ex. services faisant l'objet d'un abonnement, préférences utilisateur ou profils utilisateurTransfert de données utilisateur ou abonné
As described herein, a system, method, and computer program are provided for test-related automatic tracing. A new requirement defined for an application is identified. The new requirement is processed, using a machine learning model, to predict each portion of the new requirement covered by existing test features. One or more new test features are caused to be created for the new requirement, based on the prediction of each portion of the new requirement covered by existing test features.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06N 5/04 - Modèles d’inférence ou de raisonnement
As described herein, a system, method, and computer program are provided for using machine learning to make intelligent vendor recommendations. In use, a service to be provided at a specified location is identified. A plurality of vendors available to provide the service at the specified location are identified. A plurality of machine learning models are used to make a plurality of predictions for each vendor of the plurality of vendors, the plurality of predictions being associated with the vendor providing the service at the specified location. A vendor of the plurality of vendors is selected for provisioning the service at the specified location, based on the plurality of predictions made for each vendor of the plurality of vendors.
G06Q 10/0637 - Gestion ou analyse stratégiques, p. ex. définition d’un objectif ou d’une cible pour une organisationPlanification des actions en fonction des objectifsAnalyse ou évaluation de l’efficacité des objectifs
G06Q 30/016 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance après-vente
50.
SYSTEM, METHOD, AND COMPUTER PROGRAM FOR REAL-TIME LANGUAGE TRANSLATION USING GENERATIVE ARTIFICIAL INTELLIGENCE
As described herein, a system, method, and computer program provide real-time language translation using generative artificial intelligence. An input in a first spoken language is received. The input in the first spoken language is processed, using a generative artificial intelligence model, to generate a translation of the input in a second spoken language. The translation is output.
G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p. ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
As described herein, a system, method, and computer program provide real- time language translation using generative artificial intelligence. An input in a first spoken language is received. The input in the first spoken language is processed, using a generative artificial intelligence model, to generate a translation of the input in a second spoken language. The translation is output.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
52.
System, method, and computer program for a TOSCA modeling optimization for 5G network orchestration
As described herein, a system, method, and computer program are provided for a TOSCA modeling optimization for 5G network orchestration. A template catalog storing one or more network service instance templates is accessed, by a TOSCA-based orchestrator in a 5G network. A network service instance is deployed to the 5G network from the one or more network service instance templates, by the TOSCA-based orchestrator.
H04L 41/40 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant la virtualisation des fonctions réseau ou ressources, p. ex. entités SDN ou NFV
H04L 41/084 - Configuration en utilisant des informations préexistantes, p. ex. en utilisant des gabarits ou en copiant à partir d’autres éléments
53.
SYSTEM, METHOD, AND COMPUTER PROGRAM FOR A TOSCA MODELING OPTIMIZATION FOR 5G NETWORK ORCHESTRATION
As described herein, a system, method, and computer program are provided for a TOSCA modeling optimization for 5G network orchestration. A template catalog storing one or more network service instance templates is accessed, by a TOSCA-based orchestrator in a 5G network. A network service instance is deployed to the 5G network from the one or more network service instance templates, by the TOSCA-based orchestrator.
H04L 41/40 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant la virtualisation des fonctions réseau ou ressources, p. ex. entités SDN ou NFV
H04L 41/5041 - Gestion des services réseau, p. ex. en assurant une bonne réalisation du service conformément aux accords caractérisée par la relation temporelle entre la création et le déploiement d’un service
H04L 41/5054 - Déploiement automatique des services déclenchés par le gestionnaire de service, p. ex. la mise en œuvre du service par configuration automatique des composants réseau
54.
System, method, and computer program for unified management of multiple master-agent job execution environments
As described herein, a system, method, and computer program are provided for unified management of multiple master-agent job execution environments. Job scheduling information is accessed for a plurality of different environments each having a corresponding master that schedules job executions across a plurality of respective agents. Unified job scheduling management across the plurality of different environments is provided, using the job scheduling information.
As described herein, a system, method, and computer program are provided for a model driven Non-RT RIC design for O-RAN management and orchestration. One or more features of one or more onboarded Non-RT RIC applications are determined. During run-time of the Non-RT RIC, a set of components are deployed for the Non-RT RIC based on the one or more features of the one or more onboarded Non-RT RIC applications.
H04L 41/0806 - Réglages de configuration pour la configuration initiale ou l’approvisionnement, p. ex. prêt à l’emploi [plug-and-play]
H04L 41/0895 - Configuration de réseaux ou d’éléments virtualisés, p. ex. fonction réseau virtualisée ou des éléments du protocole OpenFlow
H04L 41/5041 - Gestion des services réseau, p. ex. en assurant une bonne réalisation du service conformément aux accords caractérisée par la relation temporelle entre la création et le déploiement d’un service
56.
System, method, and computer program for handling business agreement updates requiring orchestration when an orchestration system is unavailable
As described herein, a system, method, and computer program are provided for handling business agreement updates requiring orchestration when an orchestration system is unavailable. A signed update to a business agreement requiring orchestration by an orchestration system is received. It is determined that the orchestration system is unavailable to orchestrate requirements of the signed update to the business agreement. One or more actions are performed to handle the signed update in response to determining that the orchestration system is unavailable.
As described herein, a system, method, and computer program are provided for a media service platform. A media content is parsed to a directed graph, where vertices of the directed graph correspond to entities in the media content and edges of the directed graph define relationships between the entities. One or more creative media capability services are provided, using the directed graph.
As described herein, a system, method, and computer program are provided for a machine-learning model-agnostic cloud-agnostic no-code onboarding platform. In use, a universal unified interface to a Model-Agnostic Onboarding Workflow (MAOW) platform is provided, wherein the MAOW platform is configured as a no-code, model-agnostic, cloud-agnostic platform. Additionally, at least one machine learning model is onboarded using the MAOW platform, based on the universal unified interface. Further, the at least one machine learning model is deployed from the MAOW platform to at least one target environment.
As described herein, a system, method, and computer program are provided for creating a computer program from natural language input. Input is received from a natural language processor. The input is processed, using a machine learning model, to predict an intent of the input. A validation of the intent is performed. The intent is automatically converted to one or more executable computer commands, based on a result of the validation of the intent. The one or more executable computer commands are executed to generate a computer program.
As described herein, a system, method, and computer program are provided for identifying foreign keys between distinct tables based on a statistical analysis of table values. In use, a plurality of candidate field combinations are determined between a first table and a second table. A statistical analysis of values stored in fields of each candidate field combination of the plurality of the candidate field combinations is performed. Foreign keys between the first table and the second table are identified, based on a result of the statistical analysis.
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 17/18 - Opérations mathématiques complexes pour l'évaluation de données statistiques
61.
System, method, and computer program for managing navigational flows between application pages
As described herein, a system, method, and computer program are provided for managing a navigational flow of an application. A navigational flow defined for a plurality of user interfaces of an application is determined. The navigational flow is rendered in an editing tool. An update to the navigational flow is received, via the editing tool. The update is automatically translated into code of the application.
As described herein, a system, method, and computer program are provided for network experience optimization using a residential network router. In use, an electronic calendar is accessed by a residential network router. Additionally, the residential network router determines a plurality of events saved to the electronic calendar, wherein the plurality of events require, at least in part, simultaneous network resource (e.g. bandwidth) usage. Further, the plurality of events are prioritized, using the residential network router. Still yet, available network resources are assigned among the plurality of events, using the residential network router, based on the prioritization.
G06Q 10/101 - Création collaborative, p. ex. développement conjoint de produits ou de services
G06Q 10/109 - Gestion du temps, p. ex. agendas, rappels, réunions ou décompte de temps
H04L 12/18 - Dispositions pour la fourniture de services particuliers aux abonnés pour la diffusion ou les conférences
H04L 47/70 - Contrôle d'admissionAllocation des ressources
H04L 67/61 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en tenant compte de la qualité de service [QoS] ou des exigences de priorité
63.
System, method, and computer program for dynamic charge computation
As described herein, a system, method, and computer program are provided for dynamic charge computation. In use, a change made to a subscription of a customer is detected, wherein the subscription is associated with a billing cycle. Further, responsive to detecting the change and prior to an end of the billing cycle, at least one charge is computed for the subscription.
As described herein, a system, method, and computer program are provided for blockchain-based entity group management. An instance of a blockchain is maintained for each entity group of a plurality of defined entity groups. Further, the instance of the blockchain maintained for each entity group of the plurality of defined entity groups is utilized to manage group membership for the entity group, and control access by members of the entity group to a plurality of services having functionality configured for the plurality of defined entity groups.
As described herein, a system, method, and computer program are provided for proactive 5G leg estimation. During an initial access procedure by a user equipment on a 4G leg of a 4G-LTE network, an eNodeB of the 4G-LTE network computes a parameter for the user equipment. Further, the eNodeB of the 4G-LTE network conditionally allows an addition of a 5G leg to the 4G-LTE network for the user equipment, based on the parameter computed for the user equipment.
As described herein, a system, method, and computer program are provided for presenting tree data structures in tables. In use, a forest data structure storing data is identified. Additionally, the forest data structure is converted to a plurality of matrices. Further, the plurality of matrices are used to present the data in a table.
As described herein service brokers are used to manage the lifecycle of backing services. In use, a service catalog of backing services available for use by an application is provided. Further, one or more service brokers are used to manage a lifecycle of the backing services.
G06F 3/00 - Dispositions d'entrée pour le transfert de données destinées à être traitées sous une forme maniable par le calculateurDispositions de sortie pour le transfert de données de l'unité de traitement à l'unité de sortie, p. ex. dispositions d'interface
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
As described herein, a system, method, and computer program are provided for an exactly once messaging protocol in a publish-subscribe messaging system. A consumer (i.e. subscriber) of a publish-subscribe messaging system is identified. For each required consumer, and for each subscribed topic of the consumer, a new dedicated consumer is created for the topic in the publish-subscribe messaging system. The new dedicated consumer is used to ensure that messages published to the topic are delivered exactly once to each associated consumer.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p. ex. pour le traitement simultané de plusieurs programmes
H04L 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation
As described herein, a system, method, and computer program are provided for securing container images. In use, a request to access a container image is identified. In response to the request, a digest of the container image is retrieved. The digest is validated according to an execution and business context. A response to the request is provided, based on a result of the validating.
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
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
70.
System, method, and computer program for AWS autoscaling of Tuxedo systems
As described herein, a system, method, and computer program are provided for AWS autoscaling of Tuxedo systems. In use, an AWS cloud based deployment of a Tuxedo system is identified. Further, autoscaling of the Tuxedo system is provided in accordance with an autoscaling configuration of the AWS, using a Tuxedo registrar that maps AWS EC2 DNS names or internet protocol (IP) addresses with Tuxedo-compliant names capable of being used by the Tuxedo system.
H04L 41/00 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets
H04L 47/125 - Prévention de la congestionRécupération de la congestion en équilibrant la charge, p. ex. par ingénierie de trafic
H04L 61/10 - Correspondance entre adresses de types différents
H04L 61/3015 - Enregistrement, génération ou allocation de nom
H04L 61/4511 - Répertoires de réseauCorrespondance nom-adresse en utilisant des répertoires normalisésRépertoires de réseauCorrespondance nom-adresse en utilisant des protocoles normalisés d'accès aux répertoires en utilisant le système de noms de domaine [DNS]
71.
System, method, and computer program for generating a context visualization during test automation
As described herein, a system, method, and computer program are provided for generating a context visualization during test automation. In use, during automated testing of a user interface application, an inspection of an element within a user interface of the user interface application is detected. Additionally, in response to detecting the inspection of the element, a visualization of the element within the user interface is generated. Further, the visualization of the element within the user interface is presented with information associated with the inspection of the element.
As described herein, a system, method, and computer program are provided for a model driven Non-RT RIC design for O-RAN management and orchestration. One or more features of one or more onboarded Non-RT RIC applications are determined. During run-time of the Non-RT RIC, a set of components are deployed for the Non-RT RIC based on the one or more features of the one or more onboarded Non-RT RIC applications.
As described herein, a system, method, and computer program are provided for using metric valuations in anomaly scoring. In use, a score calculated for a metric used for anomaly detection is identified. Additionally, the score is weighted, based on a valuation defined for the metric, to form a weighted score. Further, at least one action is caused to be performed, based on the weighted score.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
H04L 41/147 - Analyse ou conception de réseau pour prédire le comportement du réseau
H04L 41/142 - Analyse ou conception de réseau en utilisant des méthodes statistiques ou mathématiques
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Business management consulting and advisory services in the field of communications, utilities, global computer information network, access provider, financial, and application service provider industries in connection with business process optimization services, customer management, order management, resources management, service fulfillment and provisioning, digital commerce and advertising management, partner management, and business process management; business management consulting and business management advisory services in the field of computer hardware and software system implementation and integration for others; business management consulting and advisory services in the field of revenue and billing management; computer data processing services for artificial intelligence; computer data processing services for cognitive computing; computer data processing services for cloud computing; setting up and conducting commercial exhibitions in the field of computers, computer services, information technology, artificial intelligence, cloud computing, blockchain technology, quantum computing, database management and electronic business transactions via a global computer network; business consulting services for companies regarding artificial intelligence; business consulting services for companies regarding computer systems that integrate Natural Language Processing (NLP), Computational Linguistics (CL), Information Retrieval (IR) and Machine Learning (ML) functions and capable of understanding general human queries and formulating responses; business consulting services for companies relating to cloud computing. Downloadable and recorded computer software for customer management, order management, revenue and billing management, service creation and delivery, service and resource management, service fulfillment and provisioning, service support and assurance, digital commerce and advertising management, partner management, and business process management in the communications, utilities, global computer information network, access provider, financial, and application service provider industries; Downloadable and recorded computer software that manages customer, product, service and network information, customer interactions, billing, payment and account information, and network usage data in the communications, utilities, global computer information network, access provider, financial, and application service provider industries; Downloadable computer programs and downloadable computer software for the artificial production of human speech and text; downloadable computer programs and downloadable computer software for natural language processing, generation, understanding and analysis; downloadable computer programs and downloadable computer software for machine-learning based language and speech processing software; downloadable computer chatbot software for simulating conversations; downloadable computer programs and downloadable computer software for creating and generating text; computer hardware and downloadable and recorded software for cognitive computing; computer hardware and downloadable and recorded software using artificial intelligence for machine learning; computer systems, namely, computer hardware and downloadable and recorded computer software for developing and integrating artificial intelligence, namely, machine learning, deep learning and natural language processing which are capable of collecting, organizing and analyzing data; computer systems, namely computer hardware and downloadable and recorded computer software that integrate Natural Language Processing (NLP), Computational Linguistics (CL), Information Retrieval (IR) and Machine Learning (ML) functions for understanding general human queries and formulating responses; electronic publications recorded on computer media, namely, user manuals, guide books, brochures, information sheets, written presentations and teaching materials in the field of computing, computer networks, computer storage, computer operating systems, information technology, database management, cloud computing and artificial intelligence. Technical support services, namely, troubleshooting of computer software problems in connection with customer management, order management, revenue and billing management, service creation and delivery, service fulfillment and provisioning, digital commerce and advertising management, partner management, and business process management in the communications, utilities, global computer information network, access provider, financial and application service provider industries; Providing temporary use of online non-downloadable software for use in processing and generating natural language queries; Providing temporary use of online non-downloadable software using AI (artificial intelligence) for the production of speech and text; Providing temporary use of online non-downloadable software for multi-modal machine-learning based language, text, and speech processing software; Providing temporary use of online non-downloadable software for facilitating interaction and communication between humans and AI (artificial intelligence) chatbots; Providing temporary use of online non-downloadable software for facilitating multi-modal natural language, speech, text, image, video, and sound input; Providing temporary use of online non-downloadable chatbot software for replying to questions from online customers; research and development services in the field of multi-modal computer natural language processing, artificial intelligence, and machine learning; Providing temporary use of online non-downloadable software using artificial intelligence for machine learning, natural language generation, statistical learning, mathematical learning, supervised learning, and unsupervised learning; providing information from searchable indexes and databases of information, including text, music, images, videos, software algorithms, mathematical equations, electronic documents, and databases, by means of non-downloadable chatbot software; software as a service (SaaS) services featuring software using artificial intelligence for use in software development and machine learning; software as a service (SaaS) services featuring software using cognitive computing for use in software development and machine learning; computer programming and computer programming consulting services for artificial intelligence; computer programming and computer programming consulting services for cognitive computing.
75.
System, method, and computer program for defect resolution
As described herein, a system, method, and computer program are provided for defect resolution. Information associated with a defect detected in a computer system is received. The information is processed, using a first machine learning model, to predict a source of the defect. The information and the source of the defect are processed, using a second machine learning model, to predict one or more parameters for handling the defect. One or more actions are caused to be performed to resolve the defect, based on the predicted one or more parameters for handling the defect.
G06F 11/00 - Détection d'erreursCorrection d'erreursContrôle de fonctionnement
G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
76.
System, method, and computer program for protecting against unintentional deletion of an eSIM from a mobile device
A system, method, and computer program are provided for protecting against unintentional deletion of an eSIM from a mobile device. In use, deletion of an eSIM from a mobile device is detected. Additionally, definitions of predefined scenarios indicative of unintentional deletions of eSIMs are accessed. Further, the detected deletion is analyzed, using the definitions, to determine that the detected deletion is unintentional. Still yet, a proactive care action is caused to be performed to address the unintentional deletion of the eSIM from the mobile device.
H04W 8/18 - Traitement de données utilisateur ou abonné, p. ex. services faisant l'objet d'un abonnement, préférences utilisateur ou profils utilisateurTransfert de données utilisateur ou abonné
H04W 8/20 - Transfert de données utilisateur ou abonné
As described herein, a system, method, and computer program provide a computer attack response service. In use, a notification is received that a transfer of at least one electronic file to a computing device has been detected as a potential incoming threat to the computing device. Responsive to the receiving the notification, at least one honeypot is created. Additionally, data within the at least one electronic file is accessed, using the at least one honeypot. Responsive to accessing the data within the at least one electronic file, activity associated with the incoming threat is monitored.
G06F 21/53 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p. ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p. ex. "boîte à sable" ou machine virtuelle sécurisée
G06F 21/56 - Détection ou gestion de programmes malveillants, p. ex. dispositions anti-virus
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Business management consulting and advisory services in the field of global computer information network, access provider, financial, and application service provider industries in connection with customer management, order management, resources management, service fulfillment and provisioning and partner management; business management consulting and business management advisory services in the field of computer hardware and software system implementation and integration for others; business management consulting and advisory services in the field of revenue and billing management excluding advisory and consulting services in the field of advertising and marketing.
(2) Technical support services, namely, troubleshooting of computer software problems in connection with customer management, order management, revenue and billing management, service creation and delivery, service fulfillment and provisioning, partner management, and business process management in the communications, utilities, global computer information network, access provider, financial and application service provider industries.
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Business management consulting and advisory services in the field of global computer information network, access provider, financial, and application service provider industries in connection with customer management, order management, resources management, service fulfillment and provisioning, and partner management; business management consulting and business management advisory services in the field of computer hardware and software system implementation and integration for others; business management consulting and advisory services in the field of revenue and billing management, excluding advisory and consulting services in the field of advertising and marketing. Technical support services, namely, troubleshooting of computer software problems in connection with customer management, order management, revenue and billing management, service creation and delivery, service fulfillment and provisioning, partner management, and business process management in the communications, utilities, global computer information network, access provider, financial and application service provider industries.
80.
System, method, and computer program for development driven test automation
A system, method, and computer program are provided for development driven test automation. Annotations are received for an application during development of the application. The annotations are processed to generate a test automation for the application.
As described herein, a system, method, and computer program are provided orchestrating patching of microservices. A plurality of microservice patches are detected, the plurality of microservice patches made available for a plurality of different cloud platforms each provided by a different cloud provider of a plurality of cloud providers. Further, installation of the plurality of microservice patches in a running production system is centrally managed.
G06F 8/658 - Mises à jour par incrémentMises à jour différentielles
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
As described herein, a system, method, and computer program are provided orchestrating patching of microservices. A plurality of microservice patches are detected, the plurality of microservice patches made available for a plurality of different cloud platforms each provided by a different cloud provider of a plurality of cloud providers. Further, installation of the plurality of microservice patches in a running production system is centrally managed.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
As described herein, a system, method, and computer program are provided for development driven test automation. Annotations are received for an application during development of the application. The annotations are processed to generate a test automation for the application.
As described herein, a system, method, and computer program are provided for dynamically generating assistance information for customer service agents. In use, presence of a customer at a physical retail store is identified. Additionally, information describing the customer is processed, using a machine learning model, to determine an expected outcome of an interaction with the customer occurring within the physical retail store. It is then determined that the customer is to be assisted by a customer service agent. Further, assistance information for the customer service agent is dynamically generated, based at least in part on the expected outcome of the interaction with the customer.
G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
G06Q 30/016 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance après-vente
85.
Machine learning system, method, and computer program for evaluation of customer service agents
As described herein, a machine learning system, method, and computer program are provided for evaluation of customer service agents. In use, presence of a customer at retail store is identified. Additionally, information associated with the customer is processed, using a machine learning model, to determine an expected outcome of an interaction with the customer occurring within the retail store. Further, after the interaction by an agent of the retail store with the customer, an actual outcome of the interaction is determined. Still yet, the agent is evaluated by comparing the actual outcome with the expected outcome. A result of the evaluation is then output, such as for use in assigning the agent to future in-store customers.
A system, method, and computer program are provided for processing a billing item. In use, a first dataset is collected including a plurality of records. The first dataset includes customer records, billing records (with billing item(s)) for each of the customers, and call incident records (with calling customer identification, billing record identification, and billing item identification). Additionally, a first AI-model is trained using the first dataset to recognize at least one pair of a first customer type and a first billing item type, and an associated first probability that such pair results in a call to the call-center. Further, a second dataset is collected including new billing records. The first AI-model is used to detect at least one billing record in the second dataset having probability higher than a redefined threshold probability that the customer associated with the billing record will call a call-center.
G06Q 20/12 - Architectures de paiement spécialement adaptées aux systèmes de commerce électronique
G06Q 30/016 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance après-vente
H04M 3/523 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur avec répartition ou mise en file d'attente des appels
H04M 15/00 - Dispositions de comptage, de contrôle de durée ou d'indication de durée
As described herein, a system, method, and computer program are provided for online data transfer. Content to be transferred to a destination device over a network is identified, where the content is constructed from a plurality of components. The plurality of components of the content are determined. A plurality of links corresponding to the plurality of components are retrieved, where each link of the plurality of links corresponds to a different component of the plurality of components. The plurality of links are transferred to the destination device over the network.
H04L 65/61 - Diffusion en flux de paquets multimédias pour la prise en charge des services de diffusion par flux unidirectionnel, p. ex. radio sur Internet
H04L 65/65 - Protocoles de diffusion en flux de paquets multimédias, p. ex. protocole de transport en temps réel [RTP] ou protocole de commande en temps réel [RTCP]
H04L 65/75 - Gestion des paquets du réseau multimédia
88.
System, method, and computer program for anomaly detection in time-series data with mixed seasonality
As described herein, a system, method, and computer program are provided for anomaly detection in time-series data with mixed seasonality. In use, time-series data of a mixed seasonality type is received. Additionally, the time-series data is segmented, by a defined unit of time, to form a plurality of time-series data segments. Further, the plurality of time-series data segments are processed to determine one or more patterns across the plurality of time-series data segments. Still yet, the one or more patterns are stored and used to perform pattern matching for an input time-series.
G06F 18/2413 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques basées sur les distances des motifs d'entraînement ou de référence
89.
SYSTEM, METHOD, AND COMPUTER PROGRAM FOR GENERATING A NETWORK SLICE EXPERIENCE INDEX FOR EVALUATING A NETWORK SLICE
As described herein, a system, method, and computer program are provided for generating a network slice experience index for evaluating a network slice. In use, a guaranteed quality of experience (QoE) is determined for a slice of a network. For at least one point in time, an actual QoE of the network overall is measured. A slice experience index is generated based on a delta between the guaranteed QoE and the actual QoE. The slice of the network is evaluated using the slice experience index.
H04L 41/5009 - Détermination des paramètres de rendement du niveau de service ou violations des contrats de niveau de service, p. ex. violations du temps de réponse convenu ou du temps moyen entre l’échec [MTBF]
90.
System, method, and computer program for unobtrusive propagation of solutions for detected incidents in computer applications
As described herein, a system, method, and computer program are provided for unobtrusive propagation of solutions for detected incidents in computer applications. A plurality of incidents detected in association with execution of at least one application are identified, the plurality of incidents being detected for the purpose of being addressed with a solution. The plurality of incidents are aggregated to identify one or more unique incidents. For each unique incident of the one or more unique incidents, at least one of machine learning or natural language processing is used to generate a plurality of ranked solutions for the unique incident, a selection of one solution of the plurality of ranked solutions is received, and the selected solution is deployed to one or more environments on which the unique incident was detected, utilizing a blockchain.
H04L 43/0823 - Erreurs, p. ex. erreurs de transmission
G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
G06F 21/50 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation
H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
91.
SYSTEM, METHOD, AND COMPUTER PROGRAM FOR INTELLIGENT SELF-HEALING OPTIMIZATION FOR FALLOUT REDUCTION
As described herein, a system, method, and computer program are provided for intelligent self-healing optimization for fallout reduction. A set of self-healing rules are stored that are configured to provide resolutions to failures detected in a computer process. Data associated with use of the self-healing rules is collected. The data is processed using a machine learning model to generate one or more recommendations for optimizing the set of self-healing rules. The one or more recommendations are output.
As described herein, a system, method, and computer program are provided for unobtrusive propagation of solutions for detected incidents in computer applications. A plurality of incidents detected in association with execution of at least one application are identified, the plurality of incidents being detected for the purpose of being addressed with a solution. The plurality of incidents are aggregated to identify one or more unique incidents. For each unique incident of the one or more unique incidents, at least one of machine learning or natural language processing is used to generate a plurality of ranked solutions for the unique incident, a selection of one solution of the plurality of ranked solutions is received, and the selected solution is deployed to one or more environments on which the unique incident was detected, utilizing a blockchain.
G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
As described herein, a system, method, and computer program are provided for using machine learning to make site specific 5G network recommendations. In use, data associated with a 5G network deployment at a particular site is collected. Further, the data is processed using a machine learning model to generate one or more recommendations for at least one of products or services capable of being used with the 5G network deployment.
As described herein, a system, method, and computer program are provided for intelligent self-healing optimization for fallout reduction. A set of self-healing rules are stored that are configured to provide resolutions to failures detected in a computer process. Data associated with use of the self-healing rules is collected. The data is processed using a machine learning model to generate one or more recommendations for optimizing the set of self-healing rules. The one or more recommendations are output.
As described herein, a system, method, and computer program are provided for using machine learning to make site specific 5G network recommendations. In use, data associated with a 5G network deployment at a particular site is collected. Further, the data is processed using a machine learning model to generate one or more recommendations for at least one of products or services capable of being used with the 5G network deployment.
As described herein, a system, method, and computer program are provided for intelligent value stream management. In use, a questionnaire is generated for a plurality of customers of an organization, wherein the organization provides a platform running a plurality of services for use by the customers. The plurality of customers are provided with access to the questionnaire. Answers to the questionnaire are received from at least one customer of the plurality of customers. Data associated with actual usage of the plurality of services is collected. The answers received from the at least one customer and the collected data are processed, using a machine learning model, to predict at least one change to be made with respect to the plurality of services.
As described herein, a system, method, and computer program are provided for intelligent value stream management. In use, a questionnaire is generated for a plurality of customers of an organization, wherein the organization provides a platform running a plurality of services for use by the customers. The plurality of customers are provided with access to the questionnaire. Answers to the questionnaire are received from at least one customer of the plurality of customers. Data associated with actual usage of the plurality of services is collected. The answers received from the at least one customer and the collected data are processed, using a machine learning model, to predict at least one change to be made with respect to the plurality of services.
As described herein, a system, method, and computer program are provided for using shared customer data and artificial intelligence to predict customer classifications. A first system of a first business entity receives an artificial intelligence model generated using output of a secure multi-party computation applied to: a first schema of first customer data stored by the first system, and a second schema of second customer data stored by a second system of a second business entity. Additionally, the first system executes the artificial intelligence model on the first customer data stored by the first system to generate a predictor, the predictor configured to receive input and process the input to predict a classification for the input. Further, the first system distributes the predictor for use by the second system of the second business entity to predict at least one classification for the second customer data.
As described herein, a system, method, and computer program are provided for smart user alert messaging. In use, raw information associated with usage of a communication service by a customer is identified. Additionally, the raw information is processed, using artificial intelligence, to infer one or more aspects of a status of the customer. Further, one or more alerts is generated for the customer, based on the raw information and the one or more aspects of the status of the customer.
A system, method, and computer program are provided for smart user alert messaging. In use, raw information associated with usage of a communication service by a customer is identified. Additionally, the raw information is processed, using artificial intelligence, to infer one or more aspects of a status of the customer. Further, one or more alerts are generated for the customer, based on the raw information and the one or more aspects of the status of the customer.
