Data Mining Weblog Neural Networks Adaptive Resonance Theory
Institute of Information Theories and Applications FOI ITHEA
Categorising visitors based on their interaction with a website is a key problem in Web content
usage. The clickstreams generated by various users often follow distinct patterns, the knowledge of which
may help in providing customised content. This paper proposes an approach to clustering weblog data, based
on ART2 neural networks. Due to the characteristics of the ART2 neural network model, the proposed
approach can be used for unsupervised and self-learning data mining, which makes it adaptable to
dynamically changing websites.