ShanghaiTech University Knowledge Management System
Unsupervised neural dependency parsing | |
2016 | |
Source Publication | 2016 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING, EMNLP 2016
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Pages | 763-771 |
Status | 已发表 |
Abstract | Unsupervised dependency parsing aims to learn a dependency grammar from text annotated with only POS tags. Various features and inductive biases are often used to incorporate prior knowledge into learning. One useful type of prior information is that there exist correlations between the parameters of grammar rules involving different POS tags. Previous work employed manually designed features or special prior distributions to encode such information. In this paper, we propose a novel approach to unsupervised dependency parsing that uses a neural model to predict grammar rule probabilities based on distributed representation of POS tags. The distributed representation is automatically learned from data and captures the correlations between POS tags. Our experiments show that our approach outperforms previous approaches utilizing POS correlations and is competitive with recent state-of-the-art approaches on nine different languages. |
Conference Place | Austin, TX, United states |
Indexed By | EI |
Language | 英语 |
Funding Project | National Natural Science Foundation of China[61503248] |
Publisher | Association for Computational Linguistics (ACL) |
EI Accession Number | 20194107499800 |
EI Keywords | Natural language processing systems |
EI Classification Number | Computer Programming Languages:723.1.1 ; Data Processing and Image Processing:723.2 |
Original Document Type | Conference article (CA) |
Document Type | 会议论文 |
Identifier | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/29539 |
Collection | 信息科学与技术学院_博士生 信息科学与技术学院_PI研究组_屠可伟组 |
Affiliation | School of Information Science and Technology, ShanghaiTech University, Shanghai, China |
First Author Affilication | School of Information Science and Technology |
First Signature Affilication | School of Information Science and Technology |
Recommended Citation GB/T 7714 | Jiang, Yong,Han, Wenjuan,Tu, Kewei. Unsupervised neural dependency parsing[C]:Association for Computational Linguistics (ACL),2016:763-771. |
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