A document retrieval model based on term frequency ranks

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Scopus citations

Abstract

This paper introduces a new full-text document retrieval model that is based on comparing occurrence frequency rank numbers of terms in queries and documents. More precisely, to compute the similarity between a query and a document, this new model first ranks the terms in the query and in the document on decreasing occurrence frequency. Next, for each term, it computes a local similarity between the query and the document, by calculating a weighted difference between the term's rank number in the query and its rank number in the document. Finally, it collects all those local similarities and unifies them into one global similarity between the query and the document. In this paper we also demonstrate that the effectiveness of this new full-text document retrieval model is comparable with that of the standard vector-space retrieval model.

Original languageEnglish
Title of host publicationProceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1994
EditorsW. Bruce Croft, C. J. van Rijsbergen
PublisherAssociation for Computing Machinery, Inc
Pages163-172
Number of pages10
ISBN (Electronic)038719889X, 9780387198897
DOIs
StatePublished - Aug 1 1994
Externally publishedYes
Event17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1994 - Dublin, Ireland
Duration: Jul 3 1994Jul 6 1994

Publication series

NameProceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1994

Conference

Conference17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1994
Country/TerritoryIreland
CityDublin
Period07/3/9407/6/94

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