A Co-occurrence based Vector Space Model for Document Indexing
Nan Feng · Zhongwen xinxi xuebao · 2012
This paper presents a novel co-occurrence terms based vector space model(CTVSM) for automatic document indexing which is inspired by the Vector Space Model(VSM).In contrast to the traditional VSM which presents the document with a bag of words regardless the position of these words in the texts,the proposed technique uses the co-occurrence terms instead of the single term.Firstly the pairs of obvious co-occurrence terms are extracted from the document set by association rules,and then the similarity between documents is also defined in this paper.The experiments indicate substantial and consistent improvements of the CTVSM over standard VSM.