Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
Topic modeling has been a key problem for document analysis. One of the canonical approaches for topic modeling is Probabilistic Latent Semantic Indexing, which maximizes the join...
Deng Cai, Qiaozhu Mei, Jiawei Han, Chengxiang Zhai
During the last decade, sequential pattern mining has been the core of numerous researches. It is now possible to efficiently discover users’ behavior in various domains such a...
A naive Bayesian classifier is a probabilistic classifier based on Bayesian decision theory with naive independence assumptions, which is often used for ranking or constructing a...
Making effective use of computational Grids requires scheduling Grid applications onto resources that best match them. Resource-related state (e.g., load, availability, and locati...
Ronak Desai, Sameer Tilak, Bhavin Gandhi, Michael ...