A comparison of SOM based document categorization systems
Xiao Luo, Nur Zincir-Heywood · 2004
This paper describes the development and evaluation of two unsupervised learning mechanisms for solving the automatic document categorization problem. Both mechanisms are based on a hierarchical structure of self-organizing feature maps. Specifically, one architecture is based on the vector space model whereas the other one is based on a code-books model. Results show that the latter architecture performs better than the first one which is based on the quality of the returned clusters.