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The Generalized vector space model is a generalization of the vector space model used in information retrieval. Wong ''et al.'' presented an analysis of the problems that the pairwise orthogonality assumption of the vector space model (VSM) creates. From here they extended the VSM to the generalized vector space model (GVSM). ==Definitions== GVSM introduces a term to term correlations, which deprecate the pairwise orthogonality assumption. More specifically, the factor considered a new space, where each term vector ''ti'' was expressed as a linear combination of ''2n'' vectors ''mr'' where ''r = 1...2n''. For a document ''dk'' and a query ''q'' the similarity function now becomes: : where ''ti'' and ''tj'' are now vectors of a ''2n'' dimensional space. Term correlation can be implemented in several ways. For an example, Wong et al. uses the term occurrence frequency matrix obtained from automatic indexing as input to their algorithm. The term occurrence and the output is the term correlation between any pair of index terms. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「generalized vector space model」の詳細全文を読む スポンサード リンク
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