Invention Grant
- Patent Title: Predicting entities for search query results
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Application No.: US16049559Application Date: 2018-07-30
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Publication No.: US10970336B2Publication Date: 2021-04-06
- Inventor: Guillaume Jean Mathieu Kempf , Marc Brette
- Applicant: salesforce.com, inc.
- Applicant Address: US CA San Francisco
- Assignee: salesforce.com, inc.
- Current Assignee: salesforce.com, inc.
- Current Assignee Address: US CA San Francisco
- Agency: Haynes and Boone, LLP
- Main IPC: G06F16/903
- 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.
Public/Granted literature
- US20200034493A1 PREDICTING ENTITIES FOR SEARCH QUERY RESULTS Public/Granted day:2020-01-30
Information query