TCS: a shell for content-based text categorization
Proceedings of the sixth conference on Artificial intelligence applications
Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Adaptive resonance associative map
Neural Networks
Training algorithms for linear text classifiers
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Towards personalised web intelligence
Knowledge and Information Systems
Classified ranking of semantic content filtered output using self-organizing neural networks
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
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This article presents a new information management method called user-configurable clustering that integrates the flexibility of clustering systems in handling novel data and the ease of use of categorization systems in providing structure. Based on a predictive self-organizing network that performs synchronized clustering of information and preference vectors, a user can influence the clustering of information vectors by encoding his/her preferences as preference vectors. We illustrate a sample session to show how a user may create and personalize an information portfolio according to his/her preferences and how the system discovers novel information groupings while organizing familiar information according to user-defined themes.