Invention Grant
- Patent Title: Evaluating personalized recommendation models
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Application No.: US14843078Application Date: 2015-09-02
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Publication No.: US10572820B2Publication Date: 2020-02-25
- Inventor: Arun Kumar Jagota , Stanislav Georgiev
- 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: Dergosits & Noah LLP
- Agent Todd A. Noah
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F16/9535 ; G06F16/335

Abstract:
A personalized recommendation model scores each object in an interaction set of objects with which a user interacted and in a ransom set of objects with which the user lacks known interaction. A system sorts each scored object based on a decreasing order of each corresponding score, and identifies a high scoring set of the sorted objects with a number (equal to the number of objects in the interaction set of objects) of highest corresponding scores. The system aggregates a corresponding order value for each object in the high scoring set that is also in the interaction set of objects (the corresponding order value for an object is based on a corresponding order for the object in the high scoring set). The system evaluates the model for the user by dividing the aggregated order value by an aggregation of a corresponding order value for each object in the high scoring set.
Public/Granted literature
- US20170061325A1 EVALUATING PERSONALIZED RECOMMENDATION MODELS Public/Granted day:2017-03-02
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