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Foundations of Computational Intelligence
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SYSNO ASEP 0355771 Document Type M - Monograph Chapter R&D Document Type Monograph Chapter Title Web Data Clustering Author(s) Húsek, Dušan (UIVT-O) RID, SAI, ORCID
Pokorný, J. (CZ)
Řezanková, H. (CZ)
Snášel, V. (CZ)Source Title Foundations of Computational Intelligence, Bio-Inspired Data Mining, 4. - Berlin : Springer, 2009 / Abraham A. ; Hassanien A.E. ; de Carvalho A.P. - ISSN 1860-949X - ISBN 978-3-642-01087-3 Pages s. 325-353 Number of pages 29 s. Number of pages 398 Language eng - English Country DE - Germany Keywords clustering methods ; web environment ; neural networks Subject RIV BB - Applied Statistics, Operational Research R&D Projects 1ET100300419 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR) CEZ AV0Z10300504 - UIVT-O (2005-2011) UT WOS 000266781600014 EID SCOPUS 65549131948 DOI 10.1007/978-3-642-01088-0_14 Annotation This chapter provides a survey of some clustering methods relevant to clustering Web elements for better information access. We start with classical methods of cluster analysis that seems to be relevant in approaching the clustering of Web data. Graph clustering is also described since its methods contribute significantly to clustering Web data. The use of artificial neural networks for clustering has the same motivation. Based on previously presented material, the core of the chapter provides an overview of approaches to clustering in the Web environment. Particularly, we focus on clustering Web search results, in which clustering search engines arrange the search results into groups around a common theme. We conclude with some general considerations concerning the justification of so many clustering algorithms and their application in the Web environment. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2011
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