Invention Grant
- Patent Title: Conversational relevance modeling using convolutional neural network
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Application No.: US16316095Application Date: 2017-07-04
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Publication No.: US11593613B2Publication Date: 2023-02-28
- Inventor: Bowen Wu , Baoxun Wang , Shuang Peng , Min Zeng , Li Zhou
- Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
- Applicant Address: US WA Redmond
- Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee Address: US WA Redmond
- Agency: Newport IP, LLC
- Agent Leonard J. Hope
- Priority: CN201610534215.0 20160708
- International Application: PCT/US2017/040626 WO 20170704
- International Announcement: WO2018/009490 WO 20180111
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06F40/30 ; G06N3/08 ; G06N3/084

Abstract:
Non-limiting examples of the present disclosure describe a convolutional neural network (CNN) architecture configured to evaluate conversational relevance of query-response pairs. A CNN model is provided that can include a first branch, a second branch, and multilayer perceptron (MLP) layers. The first branch includes convolutional layers with dynamic pooling to process a query. The second branch includes convolutional layers with dynamic pooling to process candidate responses for the query. The query and the candidate responses are processed in parallel using the CNN model. The MLP layers are configured to rank query-response pairs based on conversational relevance.
Public/Granted literature
- US20210312260A1 CONVERSATIONAL RELEVANCE MODELING USING CONVOLUTIONAL NEURAL NETWORK Public/Granted day:2021-10-07
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