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....
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...
This paper proposes a novel approach to integrate heterogeneous data in P2P networks. The approach includes a tool for building P2P semantic link networks, mechanisms for peer sch...
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 ...
Complex systems exhibit emergent patterns of behavior at different levels of organization. Powerful network analysis methods, developed in physics and social sciences, have been s...
Andre Nash, Christian Bird, Earl T. Barr, Premkuma...