Affinity-Based Probabilistic Reasoning and Document Clustering on the

The World Wide Web (WWW) has become one of the fastest growing applications on the Internet today. More and more information sources have linked online through WWW, but finding information on the WWW is also a great challenge. For most of the users, the information retrieved is not well organized and the access time is considered high on the WWW currently. Therefore, there is a need to develop a good mechanism to organize and manage the tremen-dous size and various kinds of information to facilitate the functionality of a search engine for information retrieval on the WWW. In response to such a demand, we propose a Markov Model Mediator (MMM) mechanism which em-ploys the affinity-based data mining techniques to organize and manage the information sources so that the most rel-evant documents are clustered together to achieve higher recall and precision values for information retrieval on the WWW.