- 专利标题: Computation reduction using a decision tree classifier for faster neural transition-based parsing
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申请号: US17014435申请日: 2020-09-08
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公开(公告)号: US11816581B2公开(公告)日: 2023-11-14
- 发明人: Ryosuke Kohita , Daisuke Takuma
- 申请人: International Business Machines Corporation
- 申请人地址: US NY Armonk
- 专利权人: International Business Machines Corporation
- 当前专利权人: International Business Machines Corporation
- 当前专利权人地址: US NY Armonk
- 代理商 Edward P. Li
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G06N5/01 ; G06N5/04 ; G06N3/04 ; G06N20/20
摘要:
A fast neural transition-based parser. The fast neural transition-based parser includes a decision tree-based classifier and a state vector control loss function. The decision tree-based classifier is dynamically used to replace a multilayer perceptron in the fast neural transition-based parser, and the decision tree-based classifier increases speed of neural transition-based parsing. The state vector control loss function trains the fast neural transition-based parser, the state vector control loss function builds a vector space favorable for building a decision tree that is used for the decision tree-based classifier in the neural transition-based parser, and the state vector control loss function maintains accuracy of neural transition-based parsing while the decision tree-based classifier is used to increase the speed of the neural transition-based parsing while using the decision tree-based classifier to increase the speed of the neural transition-based parsing.
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