ABSTRACT
This paper describes a system designed to disambiguate person names in a set of Web pages. In our approach Web documents are represented as different sets of features or terms of different types (bag of words, URLs, names and numbers). We apply Agglomerative Vector Space clustering that uses the similarity between pairs of analogous feature sets. This system achieved a value of 66% for Fα=0.2 and a value of 48% for Fα=0.5 in the Web People Search Task at SemEval-2007 (Artiles et al., 2007).
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- UC3M_13: disambiguation of person names based on the composition of simple bags of typed terms
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