Abstract
Knowledge bases extracted from Wikipedia are particularly useful for various NLP and Semantic Web applications due to their co- verage, actuality and multilingualism. This has led to many approaches for automatic knowledge base extraction from Wikipedia. Most of these approaches rely on the English Wikipedia as it is the largest Wikipedia version. However, each Wikipedia version contains socio-cultural knowledge, i.e. knowledge with relevance for a specific culture or language. In this work, we describe a method for extracting a large set of hyponymy relations from the Wikipedia category system that can be used to acquire taxonomies in multiple languages. More specifically, we describe a set of 20 features that can be used for for Hyponymy Detection without using additional language-specific corpora. Finally, we evaluate our approach on Wikipedia in five different languages and compare the results with the WordNet taxonomy and a multilingual approach based on interwiki links of the Wikipedia.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chernov, S., Iofciu, T., Nejdl, W., Zhou, X.: Extracting Semantics Relationships between Wikipedia Categories. In: Völkel, M., Schaffert, S. (eds.) Proceedings of the First Workshop on Semantic Wikis – From Wiki To Semantics, Workshop on Semantic Wikis, ESWC 2006 (June 2006)
de Melo, G., Weikum, G.: Towards a universal wordnet by learning from combined evidence. In: Proceeding of the 18th ACM Conference on Information and Knowledge Management, CIKM 2009, New York, NY, USA, pp. 513–522 (2009)
de Melo, G., Weikum, G.: MENTA: Inducing Multilingual Taxonomies from Wikipedia. In: Proceedings of the 19th ACM Conference on Information and Knowledge Management, pp. 1099–1108 (2010)
Domínguez García, R., Rensing, C., Steinmetz, R.: Automatic acquisition of taxonomies in different languages from multiple wikipedia versions. In: To Be Published in Proceedings of the 10th International Conference on Web-Based Learning (ICWL 2011) (2011)
Domínguez García, R., Scholl, P., Steinmetz, R.: Supporting resource-based learning on the web using automatically extracted large-scale taxonomies from multiple wikipedia versions. In: Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies, p. 35. ACM (2011)
Harman, D., Liberman, M.: Tipster complete. In: Corpus number LDC93T3A, Linguistic Data Consortium, Philadelphia (1993)
Kassner, L., Nastase, V., Strube, M.: Acquiring a Taxonomy from the German Wikipedia. In: Proceedings of the International Conference on Language Resources and Evaluation. European Language Resources Association (2008)
Miller, G.A.: WordNet: A Lexical Database for English. Communications of the ACM 38, 39–41 (1995)
Mitchell, T.M.: Machine Learning. McGraw-Hill (1997)
Nastase, V., Strube, M., Boerschinger, B., Zirn, C., Elghafari, A.: WikiNet: A Very Large Scale Multi-Lingual Concept Network. In: Proceedings of the International Conference on Language Resources and Evaluation (2010)
Navigli, R., Ponzetto, S.P.: BabelNet: Building a Very Large Multilingual Semantic Network. In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pp. 216–225 (2010)
Nguyen, D.P.T., Matsuo, Y., Ishizuka, M.: Subtree Mining for Relation Extraction from Wikipedia. In: Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, pp. 125–128 (2007)
Ponzetto, S.P., Strube, M.: Deriving a Large-Scale Taxonomy from Wikipedia. In: Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, pp. 1440–1445. AAAI Press (2007)
Quinlan, J.R.: C4.5: Programs for Machine Learning (Morgan Kaufmann Series in Machine Learning), 1st edn. Morgan Kaufmann (January1993)
Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: A Core of Semantic Knowledge. In: 16th International World Wide Web Conference (WWW 2007). ACM Press, New York (2007)
Sumida, A., Torisawa, K.: Hacking Wikipedia for Hyponymy Relation Acquisition. In: Proceedings of the International Joint Conference on Natural Language Processing (2008)
Witten, I.H., Frank, E.: Data mining: practical machine learning tools and techniques, 2nd edn. Elsevier, Morgan Kaufman, Amsterdam (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Domínguez García, R., Schmidt, S., Rensing, C., Steinmetz, R. (2012). Automatic Taxonomy Extraction in Different Languages Using Wikipedia and Minimal Language-Specific Information. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2012. Lecture Notes in Computer Science, vol 7181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28604-9_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-28604-9_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28603-2
Online ISBN: 978-3-642-28604-9
eBook Packages: Computer ScienceComputer Science (R0)