ecent Advances In HNC's Context Vector Information Retrieval Technology

Over the past few years, HNC has developed a neural network based, vector space approach to text retrieval. This approach, embodied in a system called MatchPius, allows the user to retrieve information on the basis of meaning and context of a free text query. The MatchPius system uses a neural network based, constrained self-organization technique to learn word stem interrelationships directly from a training corpus, thereby eliminating the need for hand crafted linguistic knowledge bases and their often substantial maintenance requirements. This paper presents results from recent enhancements to the basic MatchPius concept. These enhancements include the development of a one step learning law that greatly reduces the amount of time and/or computational resources required to train the system, and the development of a prototype multilingual (English and Spanish) text retrieval system.