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    PROCESSING SYSTEM HAVING A MACHINE LEARNING ENGINE FOR PROVIDING A COMMON TRIP FORMAT (CTF) OUTPUT
    1.
    发明申请
    PROCESSING SYSTEM HAVING A MACHINE LEARNING ENGINE FOR PROVIDING A COMMON TRIP FORMAT (CTF) OUTPUT 审中-公开

    公开(公告)号：WO2019199493A1

    公开(公告)日：2019-10-17

    申请号：PCT/US2019/024865

    申请日：2019-03-29

    Applicant: ALLSTATE INSURANCE COMPANY

    Inventor： NAVRATIL, Zoran ,  RICE, Kevin Patrick ,  MOHNEN, Daniel Brian ,  GLICKLEY, Kevin ,  PONNALA, Nilesh ,  CHANDRAWANSHI, Rahul

    IPC: G06F15/18

    Abstract: Aspects of the disclosure relate to enhanced telematics processing systems with improved third party source data integration features and enhanced customized driving output determinations. A computing platform may receive telematics data and third party source data. The computing platform may enrich the telematics data using the third party source data. After generating the enriched telematics data, the computing platform may use machine learning algorithms and datasets to validate the enriched telematics data. The computing platform may ingest, via a batch ingestion process, the enriched telematics data. For example, the computing platform may store the enriched telematics data and generate additional enriched telematics data until expiration of a predetermined period of time. The computing platform may ingest the enriched telematics data associated with each trip. Once the enriched telematics data has been ingested, the computing platform may generate a standardized common trip format output for each trip.

    CENTRAL REPOSITORY SYSTEM WITH CUSTOMIZABLE SUBSET SCHEMA DESIGN AND SIMPLIFICATION LAYER
    2.
    发明申请
    CENTRAL REPOSITORY SYSTEM WITH CUSTOMIZABLE SUBSET SCHEMA DESIGN AND SIMPLIFICATION LAYER 审中-公开

    公开(公告)号：WO2023060032A1

    公开(公告)日：2023-04-13

    申请号：PCT/US2022/077453

    申请日：2022-10-03

    Applicant: ALLSTATE INSURANCE COMPANY

    Inventor： POLEN, Michael ,  NAVRATIL, Zoran ,  ABAYA, Maria Nina

    IPC: G06F16/21 ,  G06F16/211 ,  G06F16/212 ,  G06Q10/067

    Abstract: Methods and systems disclosed herein describe generating products using data objects and/or entities that comply with a canonical/governed model(s). The data objects and/or entities may be obtained from an enterprise model or a combination of an enterprise model and one or more local models within a central repository to generate the new product data structures. Once all the data objects and/or entities have been added to the new product, one or more simplification rules may be applied to the new product to flatten (optimize for consumption) the data structure of the product such that superfluous or extraneous code snippets may be removed, or reduced, in such a way that the product complies with the canonical model. The new product may then be exported to an executable data format, which can either be incorporated in another application or used as a standalone product.

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