Automatic text processing
A neural network for probabilistic information retrieval
SIGIR '89 Proceedings of the 12th annual international ACM SIGIR conference on Research and development in information retrieval
A neural algorithm for document clustering
Information Processing and Management: an International Journal - Special issue on parallel processing and information retrieval
A self-organizing semantic map for information retrieval
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Documents, concepts and neural networks
CASCON '93 Proceedings of the 1993 conference of the Centre for Advanced Studies on Collaborative research: distributed computing - Volume 2
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In this paper we present some experimental results on the classification of natural language documents using Kohonen's self-organizing-map neural network paradigm. We discuss, in particular, how the classification accuracy can be improved if the standard keyword representation of documents is enhanced by including specific weights, thesaurally-defined relations among keywords, and additional synonyms for keywords. We sketch the main features of a prototype of an automatic document classification system which is capable of classifying full-text documents relative to a controlled domain-specific vocabulary and thesaural relations. The described results extend earlier work on the use of neural networks for clustering semantically similar documents.