Information retrieval on Turkish texts
Date
2008-02
Authors
Can, F.
Kocberber, S.
Balcik, E.
Kaynak, C.
Ocalan, H. C.
Vursavas, O. M.
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Abstract
In this study, we investigate information retrieval (IR) on Turkish texts using a large-scale test collection that contains 408,305 documents and 72 ad hoc queries. We examine the effects of several stemming options and query-document matching functions on retrieval performance. We show that a simple word truncation approach, a word truncation approach that uses language-dependent corpus statistics, and an elaborate lemmatizer-based stemmer provide similar retrieval effectiveness in Turkish IR. We investigate the effects of a range of search conditions on the retrieval performance; these include scalability issues, query and document length effects, and the use of stop-word list in indexing. © 2007 Wiley Periodicals, Inc.
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Association for Information Science and Technology. Journal
Publisher
John Wiley & Sons, Inc.
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Language
English