A vector space model for automatic indexing. Salton, G., Wong, A., & Yang, C. S. *Communications of the ACM*, 1975. Paper abstract bibtex In a document retrieval, or other pattern matching environment where stored entities (documents) are compared with each other or with incoming patterns (search requests), it appears that the best indexing (property) space is one where each entity lies as far away from the others as possible; in these circumstances the value of an indexing system may be expressible as a function of the density of the object space; in particular, retrieval performance may correlate inversely with space density. An approach based on space density computations is used to choose an optimum indexing vocabulary for a collection of documents. Typical evaluation results are shown, demonstating the usefulness of the model.

@article{Salton1975a,
title = {A vector space model for automatic indexing},
volume = {18},
issn = {0001-0782},
url = {http://portal.acm.org/citation.cfm?id=361219.361220},
abstract = {In a document retrieval, or other pattern matching environment where stored entities (documents) are compared with each other or with incoming patterns (search requests), it appears that the best indexing (property) space is one where each entity lies as far away from the others as possible; in these circumstances the value of an indexing system may be expressible as a function of the density of the object space; in particular, retrieval performance may correlate inversely with space density. An approach based on space density computations is used to choose an optimum indexing vocabulary for a collection of documents. Typical evaluation results are shown, demonstating the usefulness of the model.},
number = {11},
journal = {Communications of the ACM},
author = {Salton, G. and Wong, A. and Yang, C. S.},
year = {1975},
keywords = {automatic indexing, automatic information retrieval, content analysis, document space, geometry, geometry ir, vector space model, vsm},
}

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