Self-organizing maps
Internet browsing and searching: user evaluations of category map and concept space techniques
Journal of the American Society for Information Science - Special topic issue: artificial intelligence techniques for emerging information systems applications
Websom for Textual Data Mining
Artificial Intelligence Review - Special issue on data mining on the Internet
A vector space model for automatic indexing
Communications of the ACM
Modern Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Term Weighting Approaches in Automatic Text Retrieval
Term Weighting Approaches in Automatic Text Retrieval
Self organization of a massive document collection
IEEE Transactions on Neural Networks
ICA and SOM in text document analysis
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
An Efficiently Focusing Large Vocabulary Language Model
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Marginal median SOM for document organization and retrieval
Neural Networks
Mining massive document collections by the WEBSOM method
Information Sciences: an International Journal - Special issue: Soft computing data mining
Adaptive topological tree structure for document organisation and visualisation
Neural Networks - 2004 Special issue: New developments in self-organizing systems
Automatic generation of concept hierarchies using WordNet
Expert Systems with Applications: An International Journal
A coarse-to-fine framework to efficiently thwart plagiarism
Pattern Recognition
Self-organising maps in document classification: a comparison with six machine learning methods
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part I
Unsupervised learning in information retrieval using NOW architectures
EUROCAST'05 Proceedings of the 10th international conference on Computer Aided Systems Theory
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A map of text documents arranged using the Self-Organizing Map (SOM) algorithm (1) is organized in a meaningful manner so that items with similar content appear at nearby locations of the 2-dimensional map display, and (2) clusters the data, resulting in an approximate model of the data distribution in the high-dimensional document space. This article describes how a document map that is automatically organized for browsing and visualization can be successfully utilized also in speeding up document retrieval. Furthermore, experiments on the well-known CISI collection [3] show significantly improved performance compared to Salton's vector space model, measured by average precision (AP) when retrieving a small, fixed number of best documents. Regarding comparison with Latent Semantic Indexing the results are inconclusive.