Dominant Student Modeling for Web Personalization
The large amount of information on the Web can play a significant role in building an efficient repository. To overcome this challenge, the authors create a considerable model called Dominant-Model based on Naive-Bayes classifier. An incoming document will be reformulated to take the same shape of their model and then this considerable model will be used as a measure to classify it to suitable class. They investigated the effect of using this model on classifying Web information. They notice some promising experimental results showing that the use of their model improves the classification accuracy in most of the cases.