- Patent Title: Symbolic priors for recurrent neural network based semantic parsing
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Application No.: US15612098Application Date: 2017-06-02
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Publication No.: US10853724B2Publication Date: 2020-12-01
- Inventor: Chunyang Xiao , Marc Dymetman
- Applicant: Xerox Corporation
- Applicant Address: US CT Norwalk
- Assignee: Xerox Corporation
- Current Assignee: Xerox Corporation
- Current Assignee Address: US CT Norwalk
- Agency: Ortiz & Lopez, PLLC
- Agent Kermit D. Lopez; Luis M. Ortiz
- Main IPC: G06N3/02
- IPC: G06N3/02 ; G06N3/08 ; G06N3/04 ; G06N7/00 ; G06F40/30 ; G06F40/216 ; G06F40/289

Abstract:
Methods, systems, and devices for semantic parsing. In an example embodiment, a method for semantic parsing can include steps, operations, or instructions such as obtaining a data pair for learning, the data pair comprising logical form data and natural utterance data; acquiring grammar for targeted logical forms among the logical form data of the data pair; modeling data comprising other available prior knowledge utilizing WFSA (Weighted Finite State Automata); combining with the targeted logical forms with the data modeled comprising the other available prior knowledge to form a background; and exploiting the background on the data pair. Note that we do not “learn” the background, but “learn” the background-RNN (Recurrent Neural Network).
Public/Granted literature
- US20180349767A1 SYMBOLIC PRIORS FOR RECURRENT NEURAL NETWORK BASED SEMANTIC PARSING Public/Granted day:2018-12-06
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