Semantic Map Based Web Search Result Visualization

Abstract

The problem of information overload has become more pressing with the emergence of the increasingly more popular Internet services. The main information retrieval mechanisms provided by the prevailing Internet Web software are based on either keyword search (e.g., Google and Yahoo) or hypertext browsing (e.g., Internet Explorer and Netscape). The research presented in this paper is aimed at providing an alternative concept-based categorization and search capability based on a combination of meta-search and self-organizing maps. Kohonen's self-organizing map is very well known as a clustering and dimension reduction tool. Clustering can be used for categorization of search results. Dimension reduction can be used for visualization and for reducing information in order to ease search.