Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/5202
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Computing | - |
dc.creator | Li, W | - |
dc.creator | Lu, Q | - |
dc.date.accessioned | 2014-12-11T08:26:11Z | - |
dc.date.available | 2014-12-11T08:26:11Z | - |
dc.identifier.isbn | 978-4-905166-02-3 | - |
dc.identifier.uri | http://hdl.handle.net/10397/5202 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute for Digital Enhancement of Cognitive Development, Waseda University | en_US |
dc.rights | © 2011 The PACLIC 25 Organizing Committee and PACLIC Steering Committee | en_US |
dc.rights | Copyright of contributed papers reserved by respective authors | en_US |
dc.rights | Copyright 2011 by Wanyin Li, Qin Lu | en_US |
dc.subject | Collocation extraction | en_US |
dc.subject | Statistical model | en_US |
dc.subject | Syntactic rules | en_US |
dc.subject | Semantic relationship | en_US |
dc.subject | Similarity calculation | en_US |
dc.subject | HowNet | en_US |
dc.title | A hybrid extraction model for Chinese noun/verb synonym bi-gram | en_US |
dc.type | Conference Paper | en_US |
dcterms.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. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Proceedings of the 25th Pacific Asia Conference on Language, Information and Computation (PACLIC 25), 16-18 Dec, Nanyang Technological University, Singapore, p. 430-439 | - |
dcterms.issued | 2011-12-16 | - |
dc.identifier.scopus | 2-s2.0-84863869937 | - |
dc.identifier.rosgroupid | r60560 | - |
dc.description.ros | 2011-2012 > Academic research: refereed > Refereed conference paper | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
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Li_Hybrid_Extraction_Bi-gram.pdf | 135.34 kB | Adobe PDF | View/Open |
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