A survey of fuzzy web mining1. (18th April 2013)

• Record Type: Journal Article
• Authors: Lin, Chun‐Wei; Hong, Tzung‐Pei
• Is Part Of: Wiley interdisciplinary reviews. Volume 3:Number 3(2013)
• Page Start: 190
• Page End: 199
• Publication Date: 2013-04-18
• Subjects: Data mining -- Periodicals; 006.31205
• DOI: 10.1002/widm.1091
• Languages: English
• ISSNs: 1942-4787

Abstract

Abstract: 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