%T An Application of Word Sense Disambiguation to Information Retrieval
%A Jason M. Whaley
%R Technical Report PCS-TR99-352
%I Dartmouth College, Computer Science
%C Hanover, NH
%D June 1999
%U http://www.cs.dartmouth.edu/reports/TR99-352.ps.Z
%X
 The problems of word sense disambiguation and document indexing for
 information retrieval have been extensively studied.  It has been
 observed that indexing using disambiguated meanings, rather than word
 stems, should improve information retrieval results. We present a new
 corpus-based algorithm for performing word sense disambiguation. The
 algorithm does not need to train on many senses of each word; it uses 
 instead the probability that certain concepts will occur together.
 That algorithm is then used to index several corpa of documents.  Our
 indexing algorithm does not generally outperform the traditional
 stem-based tf.idf model.
%Z
 Undergraduate Honors Thesis.  Advisor: Jay Aslam.