Invention Grant
- Patent Title: Content presentation based on a multi-task neural network
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Application No.: US15053448Application Date: 2016-02-25
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Publication No.: US10803377B2Publication Date: 2020-10-13
- Inventor: Anirban Roychowdhury , Trung Bui , John Kucera , Hung Bui , Hailin Jin
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Kilpatrick Townsend & Stockton LLP
- Main IPC: G06N3/02
- IPC: G06N3/02 ; G06Q30/02 ; G06N3/08 ; H04L29/08 ; H04W4/23

Abstract:
Techniques for predictively selecting a content presentation in a client-server computing environment are described. In an example, a content management system detects an interaction of a client with a server and accesses client features. Responses of the client to potential content presentations are predicted based on a multi-task neural network. The client features are mapped to input nodes and the potential content presentations are associated with tasks mapped to output nodes of the multi-task neural network. The tasks specify usages of the potential content presentations in response to the interaction with the server. In an example, the content management system selects the content presentation from the potential content presentations based on the predicted responses. For instance, the content presentation is selected based on having the highest likelihood. The content management system provides the content presentation to the client based on the task corresponding to the content presentation.
Public/Granted literature
- US20170251081A1 CONTENT PRESENTATION BASED ON A MULTI-TASK NEURAL NETWORK Public/Granted day:2017-08-31
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