Abstract
The aim of this paper is to propose a Japanese morphological error measure in order to automatically detect morphological errors when analyzing. In particular, we focused on three similarities as the measure and experimented using them. From our experimental results, it was found that the precision of one of measures was 74% and it functioned well.
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References
Asahara, M., Matsumoto, Y.: Extended models and tools for high-performance part-of-speech tagger. In: Proceedings of The 18th International Conference on Computational Linguistics, pp. 21–27 (2000)
Hara, A., et al.: Discovery of cluster structure and the clustering rules from medical database using ADG; automatically defined groups. In: Knowledge-Based Intelligent System for Healthcare. Advanced Knowledge International, pp. 51–86 (2004)
Hisamitsu, T., Niwa, Y.: Post-processing of Japanese morphological analysis using transformation rules and contextual information. IPSJ SIGNotes Natural Language Abstract 126, 55–62 (1998) (in Japanese)
Ichihara, H., et al.: Youso no junnjokannkei kara mita ruijibunn saiteki syougou kennsaku [Similar sentence retrieval using sequence relations of its elements]. In: Proceedings of the 5th Annual Conference of Natural Language Processing Society, pp. 521–524 (1999) (in Japanese)
Korfhage, R.: Information Storage and Retrieval. Wiley Computer Publishing, John Wiley & Sons, Inc, New York (1997)
Kurosawa, Y., Ichimura, T., Aizawa, T.: A description method of syntactic rules on Japanese filmscript. In: Proceedings of the 7th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, pp. 446–453 (2003)
Kurosawa, Y., Ichimura, T., Aizawa, T.: A description method of syntactic rules on filmscripts. Journal of Natural Language Processing 12(2), 25–62 (2005) (in Japanese)
Matsumoto, Y., et al.: Morphological analysis system ChaSen version 2.2.1 manual, (2000), http://chasen.aist-nara.ac.jp/
Utiyama, M.: Statistical measure for detecting errors in results of Japanese morphological analysis. IPSJ SIGNotes NL Abstract 129, 71–77 (1999) (in Japanese)
Yamamoto, E., et al.: An IR similarity measure which is tolerant for morphological variation. Journal of Natural Language Processing 10(1), 63–80 (2003) (in Japanese)
Yamamoto, E., et al.: Dynamic programming matching for large scale information retrieval. In: Proceedings of the 6th International Workshop on Information Retrieval with Asian Language, pp. 100–108 (2003)
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© 2005 Springer-Verlag Berlin Heidelberg
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Kurosawa, Y., Sakamoto, Y., Ichimura, T., Aizawa, T. (2005). An Error Measure for Japanese Morphological Analysis Using Similarity Measures. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_126
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DOI: https://doi.org/10.1007/11552413_126
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28894-7
Online ISBN: 978-3-540-31983-2
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