P-FCM: a proximity - based fuzzy clustering

作     者：Pedrycz, W Loia, V Senatore, S 

作者机构：Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2G7 Canada Polish Acad Sci Syst Res Inst PL-01447 Warsaw Poland Univ Salerno Dept Math & Informat I-84081 Baronissi SA Italy 

出 版 物：《FUZZY SETS AND SYSTEMS》 (模糊集与系)

年 卷 期：2004年第148卷第1期

页      面：21-41页

核心收录：

学科分类：07[理学] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 070101[理学-基础数学] 

基　　金：Alberta Software Engineering Research Consortium Canada Research Chair Natural Sciences and Engineering Research Council of Canada, NSERC 

主　　题：fuzzy clustering proximity measure web mining fuzzy C-means (FCM) supervision hints preference modeling proximity hints (constraints) 

摘      要：In this study, we introduce and study a proximity-based fuzzy clustering. As the name stipulates, in this mode of clustering, a structure discovery in the data is realized in an unsupervised manner and becomes augmented by a certain auxiliary supervision mechanism. The supervision mechanism introduced in this algorithm is realized via a number of proximity hints (constraints) that specify an extent to which some pairs of patterns are regarded similar or different. They are provided externally to the clustering algorithm and help in the navigation of the search through the set of patterns and this gives rise to a two-phase optimization process. Its first phase is the standard FCM while the second step is concerned with the gradient-driven minimization of the differences between the provided proximity values and those computed on a basis of the partition matrix computed at the first phase of the algorithm. The proximity type of auxiliary information is discussed in the context of Web mining where clusters of Web pages are built in presence of some proximity information provided by a user who assesses (assigns) these degrees on a basis of some personal preferences. Numeric studies involve experiments with several synthetic data and Web data (pages). (C) 2004 Elsevier B.V. All rights reserved.