This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
Latent class models (LCM) represent the high dimensional data in a smaller dimensional space in terms of latent variables. They are able to automatically discover the patterns from...
The primary goal of Web usage mining is the discovery of patterns in the navigational behavior of Web users. Standard approaches, such as clustering of user sessions and discoveri...
Web transaction data between Web visitors and Web functionalities usually convey user task-oriented behavior pattern. Mining such type of clickstream data will lead to capture usag...
Share-frequent pattern mining discovers more useful and realistic knowledge from database compared to the traditional frequent pattern mining by considering the non-binary frequen...