Websom for textual data mining

New methods that are user-friendly and efficient are needed for guidance am ong the masses of textual information available in the Internet and the Wor ld Wide Web. We have developed a method and a tool called the WEBSOM which utilizes the self-organizing map algorithm (SOM) for organizing large colle ctions of text documents onto visual document maps. The approach to process ing text is statistically oriented, computationally feasible, and scalable - over a million text documents have been ordered on a single map. In the a rticle we consider different kinds of information needs and tasks regarding organizing, visualizing, searching, categorizing and filtering textual dat a. Furthermore, we discuss and illustrate with examples how document maps c an aid in these situations. An example is presented where a document map is utilized as a tool for visualizing and filtering a stream of incoming elec tronic mail messages.