Fuzzy integration of structure adaptive SOMs for web content mining
Since exponentially growing web contains giga-bytes of web documents, users are faced with difficulty to find an appropriate web site. Using profile, information retrieval system can personalize browsing of the web by recommending suitable web sites. User's evaluation on web content cart be used to predict users' preference on web sites and construct profiles automatically. User profile represents different aspects of user's characteristics, thereby we need an ensemble of classifiers that estimate user's preference using web content labeled by user as "like" or "dislike." Fuzzy integral is a combination scheme that uses subjectively defined relevance of classifiers and structure adaptive self-organizing map (SASONI) is a variant of SOM that is useful to pattern recognition and visualization. In this paper, fuzzy integral-based ensemble of SASOMs trained independently is used to estimate user profile and tested on UCI Syskill & Webert data. Experimental results show that the proposed method can perform better than not only previous naive Bayes classifier but also majority voting of SASOMs. (C) 2004 Elsevier B.V. All rights reserved.
fuzzy integral web content mining user profile structure adaptive self-organizing map syskill & webert