Vector space model based on semantic relatedness

Abstract

Most of data-mining methods are based on the vector space model of knowledge representation. The vector space model uses the frequency of a term in order to determine its relevance in a document. Terms can be similar by semantic meaning but be lexicographically different ones, so the classification based on the frequency of terms does not give desired results in some subject areas such as the vacancies selection. The modified vector space model based on the semantic relatedness is suggested for data-mining in this area. Evaluation results show that the proposed algorithm is better then one based on the standard vector space model.