Comparison of neural models for document clustering

Abstract We compared the application of different algorithms to document clustering. The algorithms studied were Fuzzy C-Means, Fuzzy ART, Fuzzy ART for Fuzzy Clusters, Fuzzy Max-Min, and the Kohonen neural network (only the first is not a neural network). We generated a testbed from LISA, using some of the descriptors corresponding to the different records for the comparison of the results. The best results were found with Kohonen’s algorithm which also organizes the clusters topologically. We end by discussing in more detail the possibilities offered by Kohonen’s algorithm.

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