Abstract
Building a thesaurus is very costly and time-consuming task. To alleviate this problem, this paper proposes a new method for extending a thesaurus by adding taxonomic information automatically extracted from an MRD. The proposed method adopts a machine learning algorithm in acquiring rules for identifying a taxonomic relationship to minimize human-intervention. The accuracy of our method in identifying hypernyms of a noun is 89.7%, and it shows that the proposed method can be successfully applied to the problem of extending a thesaurus.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Chodorow, M.S., Byrd, R.J., Heidorn, G.E.: Extracting Semantic Hierarchies From A Large On-Line Dictionary. In: Proceedings of the 23rd Conference of the Association for Computational Linguistics (1985)
Rigau, G., Rodriguez, H., Agirre, E.: Building Accurate Semantic Taxonomies from Mololingual MRDs. In: Proceedings of the 36th Conference of the Association for Computational Linguistics (1998)
Hearst, M.A.: Automatic acquisition of hyonyms from large text corpora. In: Proceedings of the Fourteenth International Conference on Computational Linguistics (1992)
Caraballo, S.A.: Automatic construction of a hypernym-labled noun hierarchy from text. In: Proceedings of the 37th Conference of the Association for Computational Linguistics (1999)
Pereira, F., Thishby, N., Lee, L.: Distributional clustering of English words. In: Proceedings of the 31th Conference of the Association for Computational Linguistics (1993)
Roark, B., Charniak, E.: Noun-phrase co-occurrence statistics for semi-automatic semantic lexicon construction. In: Proceedings of the 36th Conference of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics (1998)
Mitchell, T.M.: Machine Learning. Carnegie Mellon University. McGraw-Hill, New York (1997)
Choi, S., Park, H.: A New Method for Inducing Korean Dependency Grammars reflecting the Characteristics of Korean Dependency Relations. In: Proceedings of the 3rd Conterence on East-Asian Language Processing and Internet Information Technology (2003)
Moon, Y., Kim, Y.: The Automatic Extraction of Hypernym in Korean. In: Preceedings of Korea Information Science Society, vol. 21(2), pp. 613–616 (1994)
Moon, Y.: The Design and Implementation of WordNet for Korean Nouns. In: Proceedings of Korea Information Science Society (1996)
Kim, M., Kim, T., Noh, B.: The Automatic Extraction of Hypernyms and the Development of WordNet Prototype for Korean Nouns using Koran MRD. In: Proceedings of Korea Information Processing Society (1995)
Jo, P., An, M., Ock, C., Lee, S.: A Semantic Hierarchy of Korean Nouns using the Definitions of Words in a Dictionary. In: Proceedings of Korea Cognition Society (1999)
Choi, Y., Chul, S.: Development of the Algorithm for the Automatic Extraction of Broad Term. In: Proceedings of Korea Information Management Society, pp. 227–230 (1998)
Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufman, San Mateo (1993), http://www.rulequest.com/Personal/
KORTERM.: KAIST language resources, http://www.korterm.or.kr/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Choi, S., Park, H. (2005). Finding Taxonomical Relation from an MRD for Thesaurus Extension. In: Dale, R., Wong, KF., Su, J., Kwong, O.Y. (eds) Natural Language Processing – IJCNLP 2005. IJCNLP 2005. Lecture Notes in Computer Science(), vol 3651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562214_32
Download citation
DOI: https://doi.org/10.1007/11562214_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29172-5
Online ISBN: 978-3-540-31724-1
eBook Packages: Computer ScienceComputer Science (R0)