Invention Grant
- Patent Title: Structural information preserving for graph-to-text generation
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Application No.: US16883475Application Date: 2020-05-26
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Publication No.: US11550997B2Publication Date: 2023-01-10
- Inventor: Linfeng Song
- Applicant: TENCENT AMERICA LLC
- Applicant Address: US CA Palo Alto
- Assignee: TENCENT AMERICA LLC
- Current Assignee: TENCENT AMERICA LLC
- Current Assignee Address: US CA Palo Alto
- Agency: Sughrue Mion, PLLC
- Main IPC: G06F40/20
- IPC: G06F40/20 ; G06F16/901 ; G06N20/00 ; G06F40/30 ; G06N3/08

Abstract:
A method, computer program, and computer system for training a graph-to-text generation network is provided. Encoded graph information corresponding to a target sentence is received, and the encoded graph information is decoded based on a biaffine attention score. One or more loss values are determined based on the decoded information, whereby the text-to-graph generation network is trained by minimizing the one or more loss values. A first loss value is generated by reconstructing one or more triple relations based on the biaffine attention score, and a second loss value predicts the graph as a linearized sequence.
Public/Granted literature
- US20210374333A1 STRUCTURAL INFORMATION PRESERVING FOR GRAPH-TO-TEXT GENERATION Public/Granted day:2021-12-02
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