World Wide Web serves as a huge, widely distributed, global information service center for news, advertisement, consumer information, financial management, education and many other information services. This profusion of resources on the WWW gives considerable interest in research community. The Web also contains a rich and dynamic collection of hyperlink information, web page access and usage information providing rich sources for data mining and information retrieval. Traditional information retrieval techniques have been applied to document gathering and organizing on the Internet and a great number of search engines and tools have been proposed and implemented. Since users still find it hard to retrieve relevant information, create new knowledge out of the information available on the web, Personalize the web and learn about the consumers or individual users, the effectiveness of these tools is not satisfactory thus indicating that the current search engines are not sufficient for Web resource discovery. The need for identifying Web access patterns, Web structures and the regularity and dynamics of Web contents provides increased research in Web Mining as the ultimate solution.
In our work we first study and propose three Web mining categories. We also explore the connection between these Web mining categories and the related Agent paradigm then to address the problems stated above we present a system called PWIS (Personalized Web Information Search Assistant) aides information workers to gather, organize track and disseminate online information. The system will help, the user to build personal information folders by gathering and organizing on-line information according to his or her needs and preferences. Applying a Fuzzy Clustering algorithm a user can personalize his/her folders in terms of the content and information structure. The personalized folders can be constantly updated by tracking relevant information and new information can be organized into appropriate folders automatically. The personalized folders can be disseminated to other users for reference purpose.
Key words: Web Mining; Fuzzy Clustering; data mining; Information Folders; Information retrieval; Web personalization.
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