RANKING TEXT SUMMARIZATION OF TECHNICAL SOLUTIONS

    公开(公告)号:US20220405315A1

    公开(公告)日:2022-12-22

    申请号:US17354136

    申请日:2021-06-22

    Abstract: An approach to ranking identified technical solutions summaries may be provided. The approach may include extracting data from technical tickets, subject matter expert reports, and online forum data. The approach may include receiving data relating to prior applications of one or more technical solutions. Steps associated with a technical solution may be included in the information from the prior application of the technical solutions and updated based on the information from prior applications of technical solutions. The approach may include generating a risk score and a cost score for the updated technical solution based on contextual factors associated with a user or machine. The approach may include enriching a static summary for the technical solution with the cost and risk score. The approach may include ranking the enriched summary against multiple potential technical solutions.

    Automated evaluation of information retrieval

    公开(公告)号:US11481404B2

    公开(公告)日:2022-10-25

    申请号:US17022204

    申请日:2020-09-16

    Abstract: A method, system, and computer program product for automated evaluation of information retrieval systems are provided. The method accesses a natural language query from a set of natural language queries. The natural language query is associated with a query difficulty level. The method generates one or more natural language responses to the natural language natural language query. Each natural language response is associated with at least one facet of the plurality of facets. The method generates a set of feedback cues. A set of search results for the natural language query are returned. The set of search results include a highest ranked natural language response of the one or more natural language responses. The method generates an evaluation result for the HCIR system for the query difficulty level based on the one or more natural language responses, the set of search results, and the set of feedback cues.

    Database optimized disaster recovery testing

    公开(公告)号:US11003523B2

    公开(公告)日:2021-05-11

    申请号:US16431728

    申请日:2019-06-04

    Abstract: An example operation may include one or more of receiving, by a disaster recovery orchestrator, configuration changes independent from a disaster recovery test schedule, from one or more monitoring agents at each of an information technology system, analyzing incremental configuration changes since a previous disaster recovery test for potential to limit a need for unnecessary disaster recovery retest, determining component level changes at each information technology system that impact disaster recovery test readiness, initiating a partial disaster recovery retest without regard to periodic disaster recovery test schedules, in response to incremental configuration changes that are at the information technology system component-level, and invoking a blockchain service to generate blockchain transactions, the blockchain transactions committing configuration changes, disaster recovery testing actions, and disaster recovery testing results to a shared ledger of a blockchain network.

    EXTRACTION OF ENTITIES HAVING DEFINED LENGTHS OF TEXT SPANS

    公开(公告)号:US20210019615A1

    公开(公告)日:2021-01-21

    申请号:US16516009

    申请日:2019-07-18

    Abstract: Systems, computer-implemented methods, and computer program products that can facilitate extraction of entities having defined lengths of text spans are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a configuration component that defines different hyperparameters of multiple artificial intelligence models, and determines target hyperparameters of an artificial intelligence model based on performance of the multiple artificial intelligence models. The computer executable components can further comprise an application component that employs the artificial intelligence model to extract one or more entities from a data source based on the target hyperparameters.

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