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    SYSTEM AND METHOD FOR SKILLS ONTOLOGY
    41.
    发明公开
    SYSTEM AND METHOD FOR SKILLS ONTOLOGY 审中-公开

    公开(公告)号：US20240020618A1

    公开(公告)日：2024-01-18

    申请号：US17867179

    申请日：2022-07-18

    Applicant: ServiceNow, Inc.

    Inventor： Manjeet Singh ,  Eric E. Schroeder ,  Jonathan Richard Crane

    IPC: G06Q10/06 ,  G06F16/36 ,  G06F40/279 ,  G06F40/211

    CPC classification number: G06Q10/06398 ,  G06Q10/063112 ,  G06F16/367 ,  G06F40/279 ,  G06F40/211

    Abstract: A skills ontology includes classes of data that define skills possessed or demonstrated by employees of an enterprise. Specifically, sets of data may be received and segmented into strings of text referred to as utterances. The utterances may be provided to an NLU service/engine, which uses NLU techniques to process the utterances to extract intents and/or entities. Skills may be identified from within the extracted entities. New skill records may be added to the skills ontology for newly extracted skills. Employee profiles of the skills ontology may also be updated based on the actions being performed. Further, the skills ontology may be utilized to identify employees having the skills associated with tasks to be performed and assign the task to an employee for completion. Once the task as been completed, skills profiles of the employee in the skills ontology may be updated to reflect performance of the task.

    System for Providing Data
    42.
    发明公开
    System for Providing Data 审中-公开

    公开(公告)号：US20230418837A1

    公开(公告)日：2023-12-28

    申请号：US18247175

    申请日：2021-09-16

    Applicant: Siemens Aktiengesellschaft

    Inventor： Rebecca Johnson ,  Steffen Lamparter ,  Anja Simon

    IPC: G06F16/27 ,  G06F16/36

    CPC classification number: G06F16/27 ,  G06F16/367

    Abstract: Various embodiments of the teachings herein include a system for automatically synchronizing and providing data for retrieval by intelligent machines and/or users. For example, the system may include: a computing unit providing a platform; an input and output unit; and an artificial intelligence passively monitoring the input and output unit and learning from the responses, adaptations and/or assessments of the user. The artificial intelligence automatically carries out synchronization, in line with the input, of the various data types, metadata and/or memory levels of the inputs and/or outputs, develops search strategies and/or makes search results available in the output unit.

    System to determine a credibility weighting for electronic records
    44.
    发明授权
    System to determine a credibility weighting for electronic records 有权

    公开(公告)号：US11853337B2

    公开(公告)日：2023-12-26

    申请号：US17347767

    申请日：2021-06-15

    Applicant: Hartford Fire Insurance Company

    Inventor： Reuben Emory Houser ,  Qiao Wang ,  Arthur Paul Drennan, III ,  Nicole Rose Sims ,  Tracey Ellen Steger

    IPC: G06F16/33 ,  G06F16/951 ,  G06F16/36

    CPC classification number: G06F16/3344 ,  G06F16/36 ,  G06F16/951

    Abstract: Text input data may be aggregated and mapped to create composite text input data for electronic records. A semantic event may be automatically detected, triggered by a semantic rule and associated semantic tag. The detected semantic event may be flagged, and a text mining result database may be updated by adding an entry to the database. An indication associated with the event may be transmitted, and a back-end application computer server may establish a hierarchy for multiple elements of the electronic records. The computer server may determine a weight variable and response variable for each element in the hierarchy and apply a hierarchical credibility weighting methodology to the elements from level 1, representing the least granular level in the hierarchy, to level n, representing the most granular level in the hierarchy, calculated recursively from level n, to determine a final estimated credibility for the electronic records.

    CHART-BASED TIME SERIES REGRESSION MODEL USER INTERFACE
    46.
    发明公开
    CHART-BASED TIME SERIES REGRESSION MODEL USER INTERFACE 审中-公开

    公开(公告)号：US20230359675A1

    公开(公告)日：2023-11-09

    申请号：US18316953

    申请日：2023-05-12

    Applicant: Palantir Technologies Inc.

    Inventor： Christopher Martin ,  David Fowler

    IPC: G06F16/904 ,  G06F16/36 ,  G06N20/10 ,  G06T11/20

    CPC classification number: G06F16/904 ,  G06F16/367 ,  G06N20/10 ,  G06T11/206 ,  G06N5/022

    Abstract: Methods and systems for providing a user interface and workflow for interacting with time series data, and applying portions of time series data sets for refining regression models. A system can present a user interface for receiving a first user input selecting a first model from a list of models for modeling the apparatus, generate and display a first chart depicting a first time series data set depicting data from a first sensor, generate and display a second chart depicting a second time series data set depicting a target output of the apparatus, receive a second user input of a portion of the first time series data set, and generate and display a third chart depicting a third time series data set depicting an output of the selected model and aligned with the second chart of the target output and updated in real-time in response to the second user input.

    System and method for testing the technical applicability of intellectual property rights
    49.
    发明授权
    System and method for testing the technical applicability of intellectual property rights 有权

    公开(公告)号：US11755796B2

    公开(公告)日：2023-09-12

    申请号：US17327986

    申请日：2021-05-24

    Applicant: Erich Netzsch GmbH & Co. Holding KG

    Inventor： Thorsten Hachmann

    IPC: G06F30/30 ,  G06F40/30 ,  G06F16/36 ,  G06F40/42 ,  G06F119/02 ,  G06F119/18

    CPC classification number: G06F30/30 ,  G06F16/367 ,  G06F40/30 ,  G06F40/42 ,  G06F2119/02 ,  G06F2119/18

    Abstract: A system for testing the technical applicability of intellectual property rights having a computational linguistics module, which is designed to receive chains of technical graphemes and/or digitized symbolic images of intellectual property right specifications as input information, and to mechanically transfer the input information into an information model, an ontology memory, which is designed to store taxonomies, which are linked via inference rules, of conceptual classified object types, a semiotics module, which is coupled to the computational linguistics module and the ontology memory and which is designed to instantiate semiotic signs included in the information model, which is generated by the computational linguistics module, using conceptual classified object types stored in the ontology memory, and to create a contextualized information model, a construction module, which is coupled to the semiotics module and which is designed to generate a CAD model from the contextualized information model created by the semiotics module, and a 3D printing device, which is coupled to the construction module and which is designed to additively manufacture a product, which is encoded by the CAD model.

    Methods and systems for reuse of data item fingerprints in generation of semantic maps
    50.
    发明授权
    Methods and systems for reuse of data item fingerprints in generation of semantic maps 有权

    公开(公告)号：US11734332B2

    公开(公告)日：2023-08-22

    申请号：US17526474

    申请日：2021-11-15

    Applicant: cortical.io AG

    Inventor： Francisco De Sousa Webber

    IPC: G06F16/00 ,  G06F16/36 ,  G06F16/33

    CPC classification number: G06F16/36 ,  G06F16/334

    Abstract: A method for using distributed representations of data items within a first set of data documents clustered in a first two-dimensional metric space to generate a cluster of distributed representations in a second two-dimensional metric space includes clustering in a first two-dimensional metric space, by a reference map generator, a set of data documents, generating a semantic map. A parser generates an enumeration of data items occurring in the set of data documents. A representation generator generates a distributed representation using occurrence information about each data item. A sparsifying module receives an identification of a maximum level of sparsity and reduces a total number of set bits within the distributed representation. The reference map generator clusters, in a second two-dimensional metric space, a set of SDRs retrieved from the SDR database and selected according to a second at least one criterion, generating a second semantic map.

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