A Review of Web Document Clustering Approaches

Nowadays, the Internet has become the largest data repository, facing the problem of information overload. Though, the web search environment is not ideal. The existence of an abundance of information, in combination with the dynamic and heterogeneous nature of the Web, makes information retrieval a difficult process for the average user. It is a valid requirement then the development of techniques that can help the users effectively organize and browse the available information, with the ultimate goal of satisfying their information need. Cluster analysis, which deals with the organization of a collection of objects into cohesive groups, can play a very important role towards the achievement of this objective. In this chapter, we present an exhaustive survey of web document clustering approaches available on the literature, classified into three main categories: text-based, link-based and hybrid. Furthermore, we present a thorough comparison of the algorithms based on the various facets of their features and functionality. Finally, based on the review of the different approaches we conclude that although clustering has been a topic for the scientific community for three decades, there are still many open issues that call for more research.

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