A Relation Extraction Method between Related Concepts using Web Search

Size: px

Start display at page:

Download "A Relation Extraction Method between Related Concepts using Web Search"

Francis Houston
7 years ago
Views:

1 DEIM Forum 2010 C1-2 Web Web Wikipedia is-a a-part-of Wikipedia Web Wikipedia Web Wikipedia Abstract A Relation Extraction Method between Related Concepts using Web Search Masumi SHIRAKAWA, Kotaro NAKAYAMA, Eiji ARAMAKI, Takahiro HARA, and Shojiro NISHIO Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University 1-5 Yamadaoka, Suita, Osaka , Japan The Center for Knowledge Structuring, The University of Tokyo Hongo, Bunkyo-ku, Tokyo , Japan {shirakawa.masumi,hara,nishio}@ist.osaka-u.ac.jp, nakayama@cks.u-tokyo.ac.jp, eiji.aramaki@gmail.com Construction of a huge scale ontology covering many named entities, domain specific terms and relations among these concepts is one of the essential technologies in the next generation Web based on semantics. In this work, we aim at automated ontology construction with a wide coverage of concepts and these relations by combining information on the Web with Wikipedia. In this paper, we propose a relation extraction method which gets pairs of co-related concepts from an association thesaurus extracted from Wikipedia and extracts relations by using Web search. Key words relation extraction, natural language processing (NLP), thesaurus, Wikipedia 1

2 1. Web [1] [2] OpenCyc 1 WordNet [3] EDR 2 is-a a-part-of Web Wikipedia Wikipedia Wikipedia Web Wikipedia [4], [5] Web Web Web 2. Wikipedia Web Wikipedia Wiki Web Web Fig. 1 Ontology reconstruction from Case Frames Wikipedia URL [6] Wikipedia DBpedia [7] YAGO [8], [9] DBpedia Wikipedia RDF (Resource Description Framework) YAGO WordNet Wikipedia WordNet [10] [11] Wikipedia is-a SVM (Support Vector Machine) Wikipedia Wikipedia Web is-a a-part-of [12], [13] 1 2

3 1 R Table 1 A list of link texts of Softbank and reliability R 2 Wikipedia Fig. 2 An example of Wikipedia Thesaurus [14] Web [15] Web 3. Web 3. 1 Web Wikipedia [4], [5] Wikipedia Wikipedia 2 iphone ipod touch iphone BlackBerry Wikipedia Web Wikipedia SoftBank SOFTBANK Softbank Web Web Web Web Wikipedia [16] Wikipedia Wikipedia 1 1 c L c l i L c M c (l i ) l i R c (l i ) 3

4 3 Web Fig. 3 An example of query generation with case particles Fig. 4 4 An example of relation extraction by analyzing responses R c (l i ) = ln(m c(l i)) ln(max(m c(l k )), l k L c (1) R c (l i ) l i c 1 M c (l i ) 1 l i Wikipedia URL R c I R c Web Web [14] Web Web AND Web Web Web 3 Web AND N Web H H I N Web SoftBank 1 CaboCha [17] MeCab [18] v v c 1 c 2 l i l j p 1 p 2 F (p 1, p 2, v) F (p 1, p 2, v) = R c 1 (l i ) + R c2 (l j ) 2 F l i l j 1 c 1 c I(p 1, p 2, v) ( ) H(p1, p 2 ) I(p 1, p 2, v) = max, 1 N (2) F (p 1, p 2, v) (3) H(p 1, p 2) p 1 p 2 N Web (3) Web I 4. Web 4

5 4. 1 Wikipedia Web 5 Web (H) (A) (B) Web [14] 1 (CFR) 2 Mean Reciprocal Rank (MRR) 0 3 Discounted Cumulative Gain (DCG) Jarvelin [19] g(1) if i = 1 dcg(i) = dcg(i 1) + g(i) otherwise log c (i) h g(i) = a b if r(i) H if r(i) A if r(i) B r(i) i g(i) r(i) dcg(i) i [14], [20] (h, a, b) = (3, 2, 0) c = 2 0 CFR MRR DCG (4) (5) Table 2 Evaluation (all concept pairs) CFR CFR MRR MRR DCG DCG Table 3 Evaluation (concept pairs relation extracted between) CFR CFR MRR MRR DCG DCG Table 4 Analysis data in the experiment Web CFR MRR CFR 2 CFR MRR MRR 5

6 Table 5 5 An example of extracted relations Table 6 6 An example of extracted wrong relations A B Berryz A B NEWS A B ZARD A B A B A B A B A B A B A B A B A B A B A B SMAP A B DCG DCG DCG Web Web 50 Web Web A B MBS A B A B F A B A B A B A B A B A B A B SMAP NEWS MBS MBS MBS MBS MBS MBS MBS is-a a-part-of 6

7 is-a a-part-of 8! 5. Wikipedia Web Wikipedia Wikipedia [4], [5] Web 2 C( ) B( ) CORE [1] vol.20 no.6 pp Nov [2] vol.19 no.2 pp Mar [3] G.A. Miller, WordNet: A Lexical Database for English, Communications of the ACM (CACM), vol.38, no.11, pp.39 41, Nov [4] Wikipedia vol.47 no.10 pp Oct [5] K. Nakayama, T. Hara, and S. Nishio, Wikipedia Mining for An Association Web Thesaurus Construction, Proceedings of International Conference on Web Information Systems Engineering (WISE), pp , Dec [6] : Wikipedia vol.22 no.5 pp Sept [7] S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak, and Z.G. Ives, DBpedia: A Nucleus for a Web of Open Data, Proceedings of International Semantic Web Conference, Asian Semantic Web Conference (ISWC/ASWC), pp , Nov [8] F.M. Suchanek, G. Kasneci, and G. Weikum, YAGO: A Core of Semantic Knowledge, Proceedings of International Conference on World Wide Web (WWW), pp , May [9] F.M. Suchanek, G. Kasneci, and G. Weikum, YAGO: A Large Ontology from Wikipedia and WordNet, Journal of Web Semantics, vol.6, no.3, pp , Sept [10] Wikipedia 14 pp Mar [11] Wikipedia 18 Web SIG-SWO-A July [12] vol.12 no.2 pp Mar [13] D. Kawahara, and S. Kurohashi, Case Frame Compilation from the Web using High-Performance Computing, Proceedings of International Conference on Language Resources and Evaluation (LREC), May [14] D vol.j91-d no.3 pp Mar [15] Web : vol.47 no.sig19(tod32) pp Dec [16] K. Nakayama, T. Hara, and S. Nishio, A Thesaurus Construction Method from Large Scale Web Dictionaries, Proceedings of IEEE International Conference on Advanced Information Networking and Applications (AINA), pp , May [17] T. Kudo, and Y. Matsumoto, Fast Methods for Kernel- Based Text Analysis, Proceedings of Meeting on Association for Computational Linguistics (ACL), pp.24 31, July [18] T. Kudo, K. Yamamoto, and Y. Matsumoto, Applying Conditional Random Fields to Japanese Morphological Analysis, Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP), pp , July [19] K. Järvelin, and J. Kekäläinen, IR Evaluation Methods for Retrieving Highly Relevant Documents, Proceedings of International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pp.41 48, July [20] K. Eguchi, Overview of the Topical Classification Task at NTCIR-4 WEB, Working Notes of the 4th NTCIR Meeting, Supplement, vol.1, no.48 55, June

THE SEMANTIC WEB AND IT`S APPLICATIONS

15-16 September 2011, BULGARIA 1 Proceedings of the International Conference on Information Technologies (InfoTech-2011) 15-16 September 2011, Bulgaria THE SEMANTIC WEB AND IT`S APPLICATIONS Dimitar Vuldzhev