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<?xml version="1.0" standalone="yes"?> <Paper uid="N03-3004"> <Title>Discriminating Among Word Senses Using McQuitty's Similarity Analysis</Title> <Section position="1" start_page="0" end_page="0" type="abstr"> <SectionTitle> Abstract </SectionTitle> <Paragraph position="0"> This paper presents an unsupervised method for discriminating among the senses of a given target word based on the context in which it occurs. Instances of a word that occur in similar contexts are grouped together via McQuitty's Similarity Analysis, an agglomerative clustering algorithm. The context in which a target word occurs is represented by surface lexical features such as unigrams, bigrams, and second order co-occurrences. This paper summarizes our approach, and describes the results of a preliminary evaluation we have carried out using data from the SENSEVAL-2 English lexical sample and the line corpus.</Paragraph> </Section> class="xml-element"></Paper>