Abstract
In present, Information retrieval systems which are simply expressed with combination between keywords and phrase search according to the direct keyword matching method to get the information which users need. But Web documents retrieval systems serve too many documents because of term ambiguity. Also it often happens that words with several meanings occur in a document, but in a rather different context from that expected by the querying person. So the user should need extra time and effort to get more close documents. To overcome these problems, in this paper we propose an information retrieval system based on the content, which connects documents according to the degree of semantic link which it express fuzzy value by fuzzy function. Also we propose an algorithm which it produce the hierarchical structure using the degree of concepts and contents among documents. As result, we are able to select and to provide user-interested documents.
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© 2004 Springer-Verlag Berlin Heidelberg
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Han, SW., Eun, HJ., Kim, YS., Kóczy, L.T. (2004). A Document Classification Algorithm Using the Fuzzy Set Theory and Hierarchical Structure of Document. In: Laganá, A., Gavrilova, M.L., Kumar, V., Mun, Y., Tan, C.J.K., Gervasi, O. (eds) Computational Science and Its Applications – ICCSA 2004. ICCSA 2004. Lecture Notes in Computer Science, vol 3043. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24707-4_16
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DOI: https://doi.org/10.1007/978-3-540-24707-4_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22054-1
Online ISBN: 978-3-540-24707-4
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