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An information retrieval approach to spelling suggestion

Published:26 April 2010Publication History

ABSTRACT

In this paper, we present a two-step language-independent spelling suggestion system. In the first step, candidate suggestions are generated using an Information Retrieval(IR) approach. In step two, candidate suggestions are re-ranked using a new string similarity measure that uses the length of the longest common substrings occurring at the beginning and end of the words. We obtained very impressive results by reranking candidate suggestions using the new similarity measure. The accuracy of first suggestion is 92.3%, 90.0% and 83.5% for Dutch, Danish and Bulgarian language datasets respectively.

References

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  2. S. J. R. Schiller N. O., Greenhall J. A. and C. A. Serial order effects in spelling errors: evidence from two dysgraphic patients. Neurocase, 7:1--14, 2001.Google ScholarGoogle ScholarCross RefCross Ref
  3. K. Sparck Jones. A statistical interpretation of term specificity and its application in retrieval. pages 132--142, 1988. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. W. J. Wilbur, W. Kim, and N. Xie. Spelling correction in the pubmed search engine. Inf. Retr., 9(5):543--564, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. An information retrieval approach to spelling suggestion

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          cover image ACM Other conferences
          WWW '10: Proceedings of the 19th international conference on World wide web
          April 2010
          1407 pages
          ISBN:9781605587998
          DOI:10.1145/1772690

          Copyright © 2010 Copyright is held by the author/owner(s)

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 26 April 2010

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