The '''Generalized vector space model''' is a generalization of the [[vector space model]] used in [[information retrieval]]. Many classifiers, especially those which are related to document or text classification, use the TFIDF basis of VSM. However, this is where the similarity between the models ends - the generalized model uses the results of the TFIDF dictionary to generate similarity metrics based on distance or angle difference, rather than centroid based classification. Wong '''Wong et al.'''<ref name="wong">{{cite | title=Generalized vector spaces model in information retrieval | url=http://doi.acm.org/10.1145/253495.253506 | first=S. K. M. | last=Wong | coauthors=Wojciech Ziarko, Patrick C. N. Wong | publisher=[[Association for Computing Machinery|SIGIR ACM]] | date=1985-06-05}}</ref> 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).
