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    CAPTURING ORGANIZATION SPECIFICITIES WITH EMBEDDINGS IN A MODEL FOR A MULTI-TENANT DATABASE SYSTEM
    1.
    发明申请
    CAPTURING ORGANIZATION SPECIFICITIES WITH EMBEDDINGS IN A MODEL FOR A MULTI-TENANT DATABASE SYSTEM 审中-公开

    公开(公告)号：US20200034685A1

    公开(公告)日：2020-01-30

    申请号：US16049649

    申请日：2018-07-30

    Applicant: salesforce.com, inc.

    Inventor： Guillaume Jean Mathieu Kempf

    IPC: G06N3/04 ,  G06F17/30 ,  G06N3/08

    Abstract: For a multi-tenant database accessible by a plurality of separate organizations, a system is provided for capturing organization specificities in a model for the multi-tenant database. The system includes a neural network. The system is configured to: receive an organization encoding for one or more separate organizations making previous search queries into the multi-tenant database; generate a vector matrix from the organization encoding to embed organization specificities for training a model of the neural network; and using the vector matrix, train the model of the neural network for processing a present search query into the multi-tenant database. In some embodiments, the model of the neural network is global across the separate organizations accessing the database.

    Capturing organization specificities with embeddings in a model for a multi-tenant database system
    3.
    发明授权
    Capturing organization specificities with embeddings in a model for a multi-tenant database system 有权

    公开(公告)号：US11328203B2

    公开(公告)日：2022-05-10

    申请号：US16049649

    申请日：2018-07-30

    Applicant: salesforce.com, inc.

    Inventor： Guillaume Jean Mathieu Kempf

    IPC: G06F16/30 ,  G06N3/04 ,  G06N3/08 ,  G06F16/951 ,  G06F16/953

    Abstract: For a multi-tenant database accessible by a plurality of separate organizations, a system is provided for capturing organization specificities in a model for the multi-tenant database. The system includes a neural network. The system is configured to: receive an organization encoding for one or more separate organizations making previous search queries into the multi-tenant database; generate a vector matrix from the organization encoding to embed organization specificities for training a model of the neural network; and using the vector matrix, train the model of the neural network for processing a present search query into the multi-tenant database. In some embodiments, the model of the neural network is global across the separate organizations accessing the database.

    Predicting entities for search query results
    6.
    发明授权
    Predicting entities for search query results 有权

    公开(公告)号：US10970336B2

    公开(公告)日：2021-04-06

    申请号：US16049559

    申请日：2018-07-30

    Applicant: salesforce.com, inc.

    Inventor： Guillaume Jean Mathieu Kempf ,  Marc Brette

    IPC: G06F16/903 ,  G06N3/02

    Abstract: For a database accessible by a plurality of separate organizations, a system is provided for predicting entities for database query results. The system includes a multi-layer neural network. The system is configured to receive a query encoding for one or more previous queries made into the database, a user entity view frequency encoding for a frequency of views by one or more users, and an organization encoding for one or more separate organizations accessing the database; and based on the query encoding, the user entity view frequency encoding, and the organization encoding, generate a neural model for predicting entities for results to a present query into the database. In some embodiments, the neural model is global across the separate organizations accessing the database.

    DETECTING AND PROCESSING CONCEPTUAL QUERIES
    7.
    发明申请
    DETECTING AND PROCESSING CONCEPTUAL QUERIES 审中-公开

    公开(公告)号：US20200349180A1

    公开(公告)日：2020-11-05

    申请号：US16399760

    申请日：2019-04-30

    Applicant: salesforce.com, inc.

    Inventor： Guillaume Jean Mathieu Kempf ,  Francisco Dellatorre Borges ,  Marc Brette

    IPC: G06F16/33 ,  G06F16/332 ,  G06F16/31 ,  G06F16/36 ,  G06N3/02 ,  G06Q30/02 ,  G06F17/27

    Abstract: Methods, systems, and devices supporting detecting and processing conceptual queries are described. A device (e.g., an application server) may receive a search query from a user device. The search query may include one or more parameters. The device may tag the search query using one or more tags associated with the one or more parameters. In some examples, the one or more tags may be determined based on a neural network. The device may determine that the search query is supported as a conceptual query based on a tag of the one or more tags corresponding to a data object stored in a database. The device may then generate a database query in a query language based on the search query, retrieve a set of results for the search query using the database query in the query language, and transmit the set of results to the user device.

    PREDICTING ENTITIES FOR SEARCH QUERY RESULTS
    8.
    发明申请
    PREDICTING ENTITIES FOR SEARCH QUERY RESULTS 审中-公开

    公开(公告)号：US20200034493A1

    公开(公告)日：2020-01-30

    申请号：US16049559

    申请日：2018-07-30

    Applicant: salesforce.com, inc.

    Inventor： Guillaume Jean Mathieu Kempf ,  Marc Brette

    IPC: G06F17/30 ,  G06N3/02

    Abstract: For a database accessible by a plurality of separate organizations, a system is provided for predicting entities for database query results. The system includes a multi-layer neural network. The system is configured to receive a query encoding for one or more previous queries made into the database, a user entity view frequency encoding for a frequency of views by one or more users, and an organization encoding for one or more separate organizations accessing the database; and based on the query encoding, the user entity view frequency encoding, and the organization encoding, generate a neural model for predicting entities for results to a present query into the database. In some embodiments, the neural model is global across the separate organizations accessing the database.

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