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New Hierarchy Technique Using Co-Occurrence Word Information

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2004)

Abstract

By the development of the computer in recent years, calculating a complex advanced processing at high speed has become possible. Moreover, a lot of linguistic knowledge is used in the natural language processing system for improving the system. Therefore, the necessity of co-occurrence word information in the natural language processing system increases further and various researches using co-occurrence word information are done. Moreover, in the natural language processing, dictionary is necessary and indispensable because the ability of the entire system is controlled by the amount and the quality of the dictionary. In this paper, the importance of co-occurrence word information in the natural language processing system was described. The classification technique of the co-occurrence word (receiving word) and the co-occurrence frequency was described and the classified group was expressed hierarchically. Moreover, this paper proposes a technique for an automatic construction system and a complete thesaurus. Experimental test operation of this system and effectiveness of the proposal technique is verified.

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References

  1. Atlam, E.-S., Fuketa, M., Morita, K., Aoe, J.: Similarity measurement using term negative weight to word Similarity. Information Processing & Management Journal 36, 717–736 (2000)

    Article  Google Scholar 

  2. Atlam, E.-S., Fuketa, M., Morita, K., Aoe, J.: Document Similarity measurement using field Association term. Information Processing & Management Journal 39, 809–824 (2003)

    Article  Google Scholar 

  3. Fuketa, M., Lee, S., Tsuji, T., Okada, M., Aoe, J.: A document Classification method by using field association words. Information Science Journal 126, 57–70 (2000)

    Article  MATH  Google Scholar 

  4. Fukumoto, F., Tsuji, J.: Cancellation of polysemy of verb based on corpus. Electronic information communication society technology research report NLC94-24, 15–22 (1994)

    Google Scholar 

  5. Hindle, D.: Noun Classification from redicate-argument structures. In: Proceedings of the 29th Annual meeting of the Association for Computational Linguistics, pp. 229–236 (1990)

    Google Scholar 

  6. Hirao, K., Matsumoto, Y.: Case frame acquisition of verb from corpus and clustering of noun. Information Processing Society of Japan research NL104-11, 79–86 (1994)

    Google Scholar 

  7. Koyama, M., Aoe, J.: High speed searching algorithm of hierarchy concept dictionary. In: The 51st national athletic meeting, vol. 7 E-2, pp. 4-235-4-236 (1995)

    Google Scholar 

  8. Kobayashi, Y., Tokunaga, K., Tanaka, H.: Analysis of compound noun that uses meaning co-occurrence information between nouns. Natural language processing 3(1), 29–43 (1996)

    Google Scholar 

  9. Li, H., Abe, N.: Clustering Words with the MDL Principle. Journal of Natural Language Processing 4(2), 71–87 (1997)

    Google Scholar 

  10. Morimoto, K., Iriguchi, H., Aoe, J.: A Retrieval Algorithm of Dictionaries by Using Two Trie Structures” (in Japanese). Trans. IEICE J76-D-II (11), 2374–2383

    Google Scholar 

  11. Morita, K., Mochizuki, H., Yoshihiro, Y., Aoe, J.: Efficient retrieval algorithm of co-occurrence information that uses trie structure. Information Processing Society of Japan thesis magazine 39(9), 2563–2571 (1998)

    Google Scholar 

  12. Yokoyama, H., Shinichiro, O.: Classification of meaning of Japanese verb that uses co-occurrence information, Electronic information communication society, pp. 1–8 (1998)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Atlam, ES., Ghada, E., Fuketa, M., Morita, K., Aoe, Ji. (2004). New Hierarchy Technique Using Co-Occurrence Word Information. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_75

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  • DOI: https://doi.org/10.1007/978-3-540-30132-5_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23318-3

  • Online ISBN: 978-3-540-30132-5

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