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 ...
Frequent patterns in program executions represent recurring sequences of events. These patterns can be used to reveal the hidden structures of a program, and ease the comprehensio...
The problem of repair and maintenance of complex systems, such as aircraft, cars and trucks is certainly a nontrivial task. Maintenance technicians must use a great amount of knowl...
Workflow mining aims to find graph-based process models based on activities, emails, and various event logs recorded in computer systems. Current workflow mining techniques mainly ...
Liqiang Geng, Scott Buffett, Bruce Hamilton, Xin W...
In this paper, we present a rule-based modelling language for constraint programming, called Rules2CP. Unlike other modelling languages, Rules2CP adopts a single knowledge represen...