Abstract
This paper presents the HMM (Hidden Markov Model) based named entity recognition method for information extraction. In Korean language, named entities have the distinct characteristics unlike other languages. Many named entities can be decomposed into more than one word. Moreover, there are contextual relationship between named entities and their surrounding words. There are many internal and external evidences in named entities. To overcome data sparseness problem, we used multi-level back-off methods. The experimental result shows the F-measure of 87.6% in the economic article domain.
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References
Bikel, D.M., Miller, S., Schwartz, R., Weischedel, R., Nymble: A High-Performance Learning Named-finder. In: Proceedings of the Fifth Conference on Applied Natural Language Processing, pp. 194–201 (1997)
Collins, M., Singer, Y.: Unsupervised Models for Named Entity Classification. EMNLP/VLC 1999 (1999)
Kim, T.H., Lee, H.S., Ha, Y.S., Lee, M.H., Myaeng, S.H.: Proper Noun Extraction Using Data Sets. In: Proceedings of the 12th Hangul and Korean Information Processing, pp. 11–18 (2000)
Lee, K.H., Lee, J.H., Choi, M.S., Kim, G.Ch.: Study on Named Entity Recognition in Korean Text. In: Proceedings of the 12th Hangul and Korean Information Processing, pp. 292–299 (2000)
Rabiner, L.R.: A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Proceedings of the IEEE 77(2), 257–286 (1989)
Sassano, M., Utsuro, T.: Named Entity Chunking Techniques in Supervised Learning for Japanese Named Entity Recognition. In: Proceedings of the 18th International Conference on Computational Linguistics, pp. 705–711 (2000)
Sekine, S., Grishman, R., Shinnou, H.: A Decision Tree Method for Finding And Classifying Names in Japanese Texts. In: Proceedings of the Sixth Workshop on Very Large Corpora (1998)
Seon, C.N., Ko, Y., Kim, J.S., Seo, J.Y.: Named Entity Recognition using Machine Learning Methods and Pattern-Selection Rules. In: NLPRS, pp. 229–236 (2001)
Uchimoto, K., Ma, Q., Murata, M., Ozakum, H., Isahara, H.: Named Entity Extraction Based on A ME Model and Transformation Rules. In: Processing of the ACL (2000)
Fukumoto, J., Shimohata, M., Masui, F., Saski, M.: Description of the Oki System as Used for MET-2. In: Proceedings of 7th Message Understanding Conference (1998)
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Yun, BH. (2007). HMM-Based Korean Named Entity Recognition for Information Extraction. In: Zhang, Z., Siekmann, J. (eds) Knowledge Science, Engineering and Management. KSEM 2007. Lecture Notes in Computer Science(), vol 4798. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76719-0_53
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DOI: https://doi.org/10.1007/978-3-540-76719-0_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76718-3
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