We propose a Web recommendation system based on a maximum entropy model. Under the maximum entropy principle, we can combine multiple levels of knowledge about users’ navigation...
Web transaction data between web visitors and web functionalities usually convey users’ task-oriented behavior patterns. Clustering web transactions, thus, may capture such infor...
This paper improves a recently-presented approach to Web Personalization, named Community Web Directories, which applies personalization techniques to Web Directories. The Web dire...
In this paper, we propose an information retrieval model called Latent Interest Semantic Map (LISM), which features retrieval composed of both Collaborative Filtering(CF) and Prob...
We propose a new method to select relevant images to the given keywords from images gathered from the Web based on the Probabilistic Latent Semantic Analysis (PLSA) model which is...