Journal of the American Society for Information Science · 1991 · 263 citations · 16 references
ComputingComputer ScienceDatabasesInformation RetrievalNatural Language ProcessingQuery ExpansionRetrieval ModelsCo-occurrence AnalysisDiscriminatory Power AssessmentDocument RetrievalRetrievalRetrieval Effectiveness Measures
Term cooccurrence data has been extensively used in document retrieval systems for the identification of indexing terms that are similar to those that have been specified in a user query: these similar terms can then be used to augment the original query statement. Despite the plausibility of this approach to query expansion, the retrieval effectiveness of the expanded queries is often no greater than, or even less than, the effectiveness of the unexpanded queries. This article demonstrates that the similar terms identified by cooccurrence data in a query expansion system tend to occur very frequently in the database that is being searched. Unfortunately, frequent terms tend to discriminate poorly between relevant and nonrelevant documents, and the general effect of query expansion is thus to add terms that do little or nothing to improve the discriminatory power of the original query. © 1991 John Wiley & Sons, Inc.
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On Relevance, Probabilistic Indexing and Information Retrieval
M. E. Maron, J. L. Kuhns · Journal of the ACM · 1960 · 901 citations · Full text
Word‐word associations in document retrieval systems
Michael Lesk · American Documentation · 1969 · 172 citations