Invention Grant
- Patent Title: Deep reinforcement learning for personalized screen content optimization
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Application No.: US16893054Application Date: 2020-06-04
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Publication No.: US11265609B2Publication Date: 2022-03-01
- Inventor: Kyle Miller
- Applicant: Rovi Guides, Inc.
- Applicant Address: US CA San Jose
- Assignee: Rovi Guides, Inc.
- Current Assignee: Rovi Guides, Inc.
- Current Assignee Address: US CA San Jose
- Agency: Haley Guiliano LLP
- Main IPC: G06F3/00
- IPC: G06F3/00 ; G06F13/00 ; H04N5/445 ; H04N21/466 ; G06N3/08

Abstract:
Systems and methods are described for selecting content item identifiers for display. The system may identify a set of content items that are likely to be requested in the future based on a history of content item requests. The system then selects a first plurality of content categories using a category selection neural net and selects a first set of recommended content items for the first plurality of content categories. The system increases a reward score for the first plurality of content categories based on receiving a request for a content item that is included in the first set of recommended content items. The system also decreases the reward score for the first plurality of content categories based on determining that the requested content item is included in the set of content items that are likely to be requested in the future. The neural net is trained based on the reward score of the first plurality of content categories to reinforce reward score maximization. The trained neural net is the used to select content items for display.
Public/Granted literature
- US20200304873A1 DEEP REINFORCEMENT LEARNING FOR PERSONALIZED SCREEN CONTENT OPTIMIZATION Public/Granted day:2020-09-24
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