Abstract
A great deal of research has been made to model the vagueness and uncertainty in information retrieval. One such research is fuzzy ranking models, which have been showing their superior performance in handling the uncertainty involved in the retrieval process. However, these conventional fuzzy ranking models are limited to incorporate the user preference when calculating the rank of documents. To address this issue, we develop a new fuzzy ranking model based on the user preference.
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© 2006 Springer-Verlag Berlin Heidelberg
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Kang, BY., Kim, DW. (2006). On Text Ranking for Information Retrieval Based on Degree of Preference. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2006. Lecture Notes in Computer Science, vol 3878. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11671299_40
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DOI: https://doi.org/10.1007/11671299_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32205-4
Online ISBN: 978-3-540-32206-1
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