Lapata, Mirella and Frank Keller. 2007. An Information Retrieval Approach to Sense Ranking. In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, 348-355. Rochester, New York.

In word sense disambiguation, choosing the most frequent sense for an ambiguous word is a powerful heuristic. However, its usefulness is restricted by the availability of sense-annotated data. In this paper, we propose an information retrieval-based method for sense ranking that does not require annotated data. The method queries a information retrieval engine to estimate the degree of association between a word and its sense descriptions. Experiments on the Senseval test materials yield state-of-the art performance. We also show that the estimated sense frequencies correlate reliably with native speakers' intuitions.

@InProceedings{Lapata:Keller:07
  author = 	 {Mirella Lapata and Frank Keller},
  title = 	 {An Information Retrieval Approach to Sense Ranking},
  crossref =	 {NAACL:07}, 
  pages =        {348--355}
}

@Proceedings{NAACL:07,
  title = 	 {Proceedings of the Human Language Technology
                  Conference of the North American Chapter of the 
                  Association for Computational Linguistics},
  booktitle =    {Proceedings of the Human Language Technology
                  Conference of the North American Chapter of the 
                  Association for Computational Linguistics},
  year = 	 2007,
  address =	 {Rochester}
}