Self-organising maps for tree view based hierarchical document clustering

In this paper, we investigate the use of self-organising maps (SOMs) for document clustering. Previous methods using SOMs to cluster documents have used 2D maps. This paper presents a hierarchical and growing method using a series of 1D maps instead. Using this type of SOM is an efficient method for clustering documents and browsing them in a dynamically generated tree of topics. These topics are automatically discovered for each cluster, based on the set of documents in a particular cluster. We demonstrate the efficiency of the method using different sets of real-world Web documents.