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http://hdl.handle.net/10397/5200
| Title: | Mining concepts from Wikipedia for ontology construction | Authors: | Cui, G Lu, Q Li, W Chen, Y |
Issue Date: | 15-Sep-2009 | Source: | 2009 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2009 : proceedings : 15-18 Sept. 2009, Università degli Studi di Milano Bicocca, Milano, Italy, v. 3, p. 287-290 | Abstract: | An ontology is a structured knowledgebase of concepts organized by relations among them. But concepts are usually mixed with their instances in the corpora for knowledge extraction. Concepts and their corresponding instances share similar features and are difficult to distinguish. In this paper, a novel approach is proposed to comprehensively obtain concepts with the help of definition sentences and Category Labels in Wikipedia pages. N-gram statistics and other NLP knowledge are used to help extracting appropriate concepts. The proposed method identified nearly 50,000 concepts from about 700,000 Wiki pages. The precision reaching 78.5% makes it an effective approach to mine concepts from Wikipedia for ontology construction. | Keywords: | Concept Ontology construction Wikipedia |
Publisher: | IEEE Computer Society | ISBN: | 978-0-7695-3801-3 (print) 978-1-4244-5331-3 (E-ISBN) |
DOI: | 10.1109/WI-IAT.2009.284 | Rights: | © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication Cui, G., Lu, Q., Li, W. & Chen, Y. (2009). Mining concepts from Wikipedia for ontology construction. Workshop on Natural Language Processing and Ontology Engineering (NLPOE 2009), Milan, Italy, Sept. 15-18, 2009 is available at http://dx.doi.org/10.1109/WI-IAT.2009.284 |
| Appears in Collections: | Conference Paper |
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| WI_cgy_v3.pdf | Pre-published version | 118.13 kB | Adobe PDF | View/Open |
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