Advertisement

A New Approach for Automatic Building Field Association Words Using Selective Passage Retrieval

  • El-Sayed Atlam
  • Elmarhomy Ghada
  • Kazuhiro Morita
  • Jun-ichi Aoe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4252)

Abstract

Large collections of full-text document are now commonly used in automated information retrieval. When the stored document texts are long, the retrieval of complete documents may not be in the users’ best interest and extract Filed Association (FA) words is not accurate. In such circumstances, efficient and effective retrieval FA words may be obtained by using passage retrieval strategies designed to retrieve text excerpts of varying size in response to statements of user interest.

New approaches are described in this study for implementing selective passage retrieval systems, and identifying text passage response to particular user needs. Moreover an automated system is using for extract accurate FAwords from that passage and evaluate the usefulness of the proposed method. From the experimental results, when passage retrieval are accessible leading to the retrieval of additional extracted relevant FA word with corresponding improvements in Recall and Precision. Therefore, Recall and Precision improved by 30% than using whole texts and traditional methods.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aoe, J., Morita, K., Mochizuki, H.: An Efficient Retrieval Algorithm of Collocate Information Using Tree Structure. Transaction of the IPSJ 39(9), 2563–2571 (1989)Google Scholar
  2. 2.
    Atlam, E.-S., Morita, K., Fuketa, M., Aoe, J.: A New Method For Selecting English Compound Terms and its Knowledge Representation. Information Processing & Management Journal 38, 807–821 (2000)CrossRefGoogle Scholar
  3. 3.
    Atlam, E.-S., Fuketa, M., Morita, K., Aoe, J.: Document Similarity measurement using Field association terms. Information Processing & Management Journal 39, 809–824 (2003)CrossRefGoogle Scholar
  4. 4.
    Atlam, E.-S., Elmarhomy, G., Fuketa, M., Morita, K., Aoe, J.-i.: Automatic building of new Field Association word candidates using search. Information Processing & Management Journal 42(4), 951–962 (2006)CrossRefGoogle Scholar
  5. 5.
    Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification and Regression Trees. Chapman and Hall, Boca Raton (1984)zbMATHGoogle Scholar
  6. 6.
    Callen, J.P.: Passage and level evidence in document retrieval. In: Proc. of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 302–310 (1994)Google Scholar
  7. 7.
    Dozawa, T.: Innovative Multi Information Dictionary Imidas 1999. Annual Series. Zueisha Publication Co., Japan (1999) (In Japanese)Google Scholar
  8. 8.
    Iwayama, M., Tokunaga, T.: Probabilistic Passage Categorization and Its Application. Journal of Natural language Processing 6(3), 181–198 (1999)Google Scholar
  9. 9.
    Kaszkiel, M., Zobel, J.: Passage retrieval revised. In: Proc. of the 20th Annual International ACM SIGIR Conference on Research and Development in information Retrieval, pp. 178–185 (1997)Google Scholar
  10. 10.
    Kawabe, K., Matsumoto, Y.: Acquisition of normal lexical knowledge based on basic level category. Information Processing Society of Japan, SIG note, NL125-9, 87–92 (1998)Google Scholar
  11. 11.
    Melucii, M.: Passage Retrieval and a Probabilistic technique. Information Processing and Management 34(1), 43–68 (1998)CrossRefGoogle Scholar
  12. 12.
    Risvik, K.M., Michelsen, R.: Search Engines and Web Dynamics. Computer Networks 39, 289–302 (2002)CrossRefGoogle Scholar
  13. 13.
    Salton, G., McGill, M.J.: Introduction of Modern Information Retrieval. McGraw-Hill, New York (1983)Google Scholar
  14. 14.
    Salton, G., Allan, J., Buckley, C.: Approaches to Passage Retrieval in Full Text Information Systems. In: The Proceedings of the 16th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 1993) (1993)Google Scholar
  15. 15.
    Salton, G.: Automatic text Processing-The Transformation, Analysis, and Retrieval of Information by Computer. Addison Wesley Publishing Company, Reading (1989)Google Scholar
  16. 16.
    Tsuji, T., Nigazawa, H., Okada, M., Aoe, J.: Early Field Recognition by Using Field Association Words. In: The Proceeding of the 18th International Conference on Computer Processing of Oriental Language, vol. 2, pp. 301–304 (1999)Google Scholar
  17. 17.
    Tsuji, T., Fuketa, M., Morita, K., Aoe, J.: An Efficient Method of Determining Field Association Terms of Compound Words. Journal of Natural Language Processing 7(2), 3–26 (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • El-Sayed Atlam
    • 1
  • Elmarhomy Ghada
    • 1
  • Kazuhiro Morita
    • 1
  • Jun-ichi Aoe
    • 1
  1. 1.Department of Information Science and Intelligent SystemsUniversity of TokushimaTokushimaJapan

Personalised recommendations