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Which "Apple" are you talking about ?

Published:21 April 2008Publication History

ABSTRACT

In a higher level task such as clustering of web results or

word sense disambiguation, knowledge of all possible distinct concepts in which an ambiguous word can be expressed would be advantageous, for instance in determining the number of clusters in case of clustering web search results. We propose an algorithm to generate such a ranked list of distinct concepts associated with an ambiguous word. Concepts which are popular in terms of usage are ranked higher.

We evaluate the coverage of the concepts inferred from our algorithm on the results retrieved by querying the ambiguous word using a major search engine and show a coverage of 85% for top 30 documents averaged over all keywords.

References

  1. S. Cucerzan. Large-scale named entity disambiguation based on Wikipedia data. In Proceedings of EMNLP-CoNLL 2007, pages 708--716, 2007.Google ScholarGoogle Scholar
  2. R. Mihalcea. Using wikipedia for automatic word sense disambiguation. NAACL, 2007.Google ScholarGoogle Scholar
  3. H.-J. Zeng, Q.-C. He, Z. Chen, W.-Y. Ma, and J. Ma. Learning to cluster web search results. SIGIR, July 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Which "Apple" are you talking about ?

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      • Published in

        cover image ACM Conferences
        WWW '08: Proceedings of the 17th international conference on World Wide Web
        April 2008
        1326 pages
        ISBN:9781605580852
        DOI:10.1145/1367497

        Copyright © 2008 ACM

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        Publication History

        • Published: 21 April 2008

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