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A survey of fuzzy web mining
Author(s) -
Lin ChunWei,
Hong TzungPei
Publication year - 2013
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.1091
Subject(s) - web mining , computer science , web intelligence , data mining , data web , web modeling , fuzzy set , fuzzy logic , the internet , web page , concept mining , world wide web , information retrieval , artificial intelligence
The Internet has become an unlimited resource of knowledge, and is thus widely used in many applications. Web mining plays an important role in discovering such knowledge. This mining can be roughly divided into three categories, including Web usage mining, Web content mining, and Web structure mining. Data and knowledge on the Web may, however, consist of imprecise, incomplete, and uncertain data. Because fuzzy‐set theory is often used to handle such data, several fuzzy Web‐mining techniques have been proposed to reveal fuzzy and linguistic knowledge. This paper reviews these techniques according to the three Web‐mining categories above—fuzzy Web usage mining, fuzzy Web content mining, and fuzzy Web structure mining. Some representative approaches in each category are introduced and compared. © 2013 Wiley Periodicals, Inc. This article is categorized under: Algorithmic Development > Web Mining Technologies > Computational Intelligence