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Corpus-based stemming using cooccurrence of word variants

Published:01 January 1998Publication History
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Abstract

Stemming is used in many information retrieval (IR) systems to reduce variant word forms to common roots. It is one of the simplest applications of natural-language processing to IR and is one of the most effective in terms of user acceptance and consistency, though small retrieval improvements. Current stemming techniques do not, however, reflect the language use in specific corpora, and this can lead to occasional serious retrieval failures. We propose a technique for using corpus-based word variant cooccurrence statistics to modify or create a stemmer. The experimental results generated using English newspaper and legal text and Spanish text demonstrate the viability of this technique and its advantages relative to conventional approaches that only employ morphological rules.

References

  1. BROGLIO, J., CALLAN, J. P., AND CROFT, W. 1994. An overview of the INQUERY system as used for the TIPSTER project. In Proceedings of the TIPSTER Workshop. Morgan-Kaufmann, San Mateo, Calif., 47-67.Google ScholarGoogle Scholar
  2. BROGLIO, J., CALLAN, J. P., CROFT, W. B., AND NACHBAR, D.W. 1995. Document retrieval and routing using the INQUERY system. In Proceedings of the 3rd Text REtrieval Conference (TREC-3), D. Harman, Ed. NIST Special Publication 500-225, 22-29.Google ScholarGoogle Scholar
  3. CHURCH, K. AND HANKS, P. 1989. Word association norms, mutual information, and lexicography. In Proceedings of the 27th ACL Meeting. 76-83. Google ScholarGoogle Scholar
  4. CROFT, W. B. AND XU, J. 1995. Corpus-specific stemming using word form co-occurrence. In the 4th Annual Symposium on Document Analysis and Information Retrieval. 147-159.Google ScholarGoogle Scholar
  5. HARMAN, D. 1991. How effective is suffixing? J. Am. Soc. Inf. Sci. 42, 1, 7-15.Google ScholarGoogle Scholar
  6. HARMAN, D. 1995. Overview of the third text REtrieval conference (TREC-3). In Proceedings of the 3rd Text REtrieval Conference (TREC-3), D. Harman, Ed. NIST Special Publication 500-225, 1-20.Google ScholarGoogle Scholar
  7. HULL, D. 1993. Using statistical testing in the evaluation of retrieval experiments. In Proceedings of the 13th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, New York, 329-338. Google ScholarGoogle Scholar
  8. HULL, D.A. 1996. Stemming algorithms: A case study for detailed evaluation. J. Am. Soc. Inf. Sci. 47, 1, 70-84. Google ScholarGoogle Scholar
  9. JING, Y. AND CROFT, W. 1994. An association thesaurus for information retrieval. In Proceedings of RIAO 94. 146-160.Google ScholarGoogle Scholar
  10. KRAAIJ, W. 1996. Viewing stemming as recall enhancement. In Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, New York, 40-48. Google ScholarGoogle Scholar
  11. K_ROVETZ, R. 1993. Viewing morphology as an inference process. In Proceedings of the 16th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, New York, 191-202. Google ScholarGoogle Scholar
  12. PoPovIc, M. AND WILLETT, P. 1992. The effectiveness of stemming for natural-language access to Slovene textual data. J. Am. Soc. Inf. Sci. 43, 5, 384-390.Google ScholarGoogle Scholar
  13. PORTER, M. 1980. An algorithm for suffix stripping. Program 14, 3, 130-137.Google ScholarGoogle Scholar
  14. SALTON, G. 1989. Automatic Text Processing. Addison-Wesley, Reading, Mass. Google ScholarGoogle Scholar
  15. SPARCK JONES, K. 1971. Automatic Keyword Classification for Information Retrieval. Archon Books, Hamden, Conn.Google ScholarGoogle Scholar
  16. TURTLE, H. 1994. Natural language vs. Boolean query evaluation: A comparison of retrieval performance. In Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, New York, 212-220. Google ScholarGoogle Scholar
  17. VAN RIJSBERGEN, C. 1979. Information Retrieval. 2nd ed. Butterworths, London, U.K. Google ScholarGoogle Scholar
  18. VOORHEES, E. 1994. Query expansion using lexical-semantic relations. In Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, New York, 61-69. Google ScholarGoogle Scholar

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