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Determining semantic similarity of two sets of words that describe two entities is an important problem in web mining (search and recommendation systems), targeted advertisement and domains that need semantic content matching. Traditional Information Retrieval approaches, even when extended to include semantics by performing the similarity comparison on concepts instead of words/terms, may not always determine the right matches when there is no direct overlap in the exact concepts that represent the semantics. As the entity descriptions are treated as self-contained units, the relationships that are not explicit in the entity descriptions are usually ignored. This notion of semantic similarity is extended to consider inherent relationships between concepts using ontologies.
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