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http://hdl.handle.net/10397/5202
| Title: | A hybrid extraction model for Chinese noun/verb synonym bi-gram | Authors: | Li, W Lu, Q |
Issue Date: | 16-Dec-2011 | Source: | Proceedings of the 25th Pacific Asia Conference on Language, Information and Computation (PACLIC 25), 16-18 Dec, Nanyang Technological University, Singapore, p. 430-439 | Abstract: | Statistical-based collocation extraction approaches suffer from (1) low precision rate because high co-occurrence bi-grams may be syntactically unrelated and are thus not true collocations; (2) low recall rate because some true collocations with low occurrences cannot be identified successfully by statistical-based models. To integrate both syntactic rules as well as semantic knowledge into a statistical model for collocation extraction is one way to achieve a high precision while keeping a reasonable recall. This paper designs a cascade system which employs a hybrid model by integrating both syntactic and semantic knowledge into a statistical model for Chinese synonymous noun/verb collocations extraction. The grammatically bounded noun/verb collocations are extracted first from a syntactic-rule based module, which is then inputted to a semantic-based module for further retrieval of low frequent bi-gram collocations. | Keywords: | Collocation extraction Statistical model Syntactic rules Semantic relationship Similarity calculation HowNet |
Publisher: | Institute for Digital Enhancement of Cognitive Development, Waseda University | ISBN: | 978-4-905166-02-3 | Rights: | © 2011 The PACLIC 25 Organizing Committee and PACLIC Steering Committee Copyright of contributed papers reserved by respective authors Copyright 2011 by Wanyin Li, Qin Lu |
| Appears in Collections: | Conference Paper |
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| Li_Hybrid_Extraction_Bi-gram.pdf | 135.34 kB | Adobe PDF | View/Open |
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