This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
Abstract—The peer-to-peer networking concept has revolutionized the cost structure of Internet data dissemination by making large scale content delivery with low server cost feas...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
Abstract—We study the ubiquitous data collection for mobile users in wireless sensor networks. People with handheld devices can easily interact with the network and collect data....
Recent years have witnessed the dramatic popularity of online social networking services, in which millions of members publicly articulate mutual "friendship" relations....