Distance-preserving projection based perturbation has gained much attention in privacy-preserving data mining in recent years since it mitigates the privacy/accuracy tradeoff by ac...
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 ...
Mining association rules and mining sequential patterns both are to discover customer purchasing behaviors from a transaction database, such that the quality of business decision ...
Eficient and efiective discovery of resource and knowledge from the Internet has become an imminent research issue, especially with the advent of the Information Super-Highway. A ...
—Modern applications such as web knowledge base, network traffic monitoring and online social networks have made available an unprecedented amount of network data with rich type...