Another look at automatic text-retrieval systems
Communications of the ACM
Automatic text processing
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
WEIRD: an approach to concept-based information retrieval
ACM SIGIR Forum
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
Nonlocal language modeling based on context co-occurrence vectors
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
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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 MatchPlus, allows the user to retrieve information on the basis of meaning and context of a free text query. The MatchPlus 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 MatchPlus 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.