A Context Vector-Based Self Organizing Map for Information Visualization

HNC Software, Inc. has developed a system called DOCUVERSE for visualizing the information content of large textual corpora. The system is built around two separate neural network methodologies context vectors and self organizing maps. Context vectors (CVs) are high dimensional information representations that encode the semantic content of the textual entities they represent. Self organizing maps (SOMs) are capable of transforming an input high dimensional signal space into a much lower (usually two or three) dimensional output space useful for visualization. Related information themes contained in the corpus, depicted graphically, are presented in spatial proximity to one another. Neither process requires human intervention, nor an external knowledge base. Together, these neural network techniques can be utilized to automatically identify the relevant information themes present in a corpus, and present those themes to the user in a intuitive visual form. TIPSTER TEXT PROGRAM PHASE II: Proceedings of a Workshop held at Vienna, Virginia, May 6-8, 1996. Sponsored by the Defense Advanced Research Projects Agency.