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Content-based implicit user modeling techniques usually employ traditional term vector as a representation of the user's interest. However, due to the problem of dimensionality in vector space model, a simple term vector is not a sufficient representation of the user model as it ignores the semantic relations between terms. In this paper, we present a novel method to enhance a traditional term-based user model with the WordNet-based semantic similarity techniques. To achieve this, we utilizedoi:10.1145/1244002.1244291 dblp:conf/sac/AchananuparpHNJ07 fatcat:64p7u2hmuffkrokf2pdwksvelm