Semantic Vectors: an Information Retrieval Scenario

In this paper we exploit Semantic Vectors to develop an IR system. The idea is to use semantic spaces built on terms and documents to overcome the problem of word ambiguity. Word ambiguity is a key issue for those systems which have access to textual information. Semantic Vectors are able to dividing the usages of a word into different meanings, discriminating among word meanings based on information found in unannotated corpora. We provide an in vivo evaluation in an Information Retrieval scenario and we compare the proposed method with another one which exploits Word Sense Disambiguation (WSD). Contrary to sense discrimination, which is the task of discriminating among different meanings (not necessarily known a priori), WSD is the task of selecting a sense for a word from a set of predefined possibilities. The goal of the evaluation is to establish how Semantic Vectors affect the retrieval performance.