Neglected conditions are an important but difficult-to-find class of software defects. This paper presents a novel approach for revealing neglected conditions that integrates stati...
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
We propose an algorithm to construct classification models with a mixture of kernels from labeled and unlabeled data. The derived classifier is a mixture of models, each based o...
Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
We describe an approach for acquiring the domain-specific dialog knowledge required to configure a task-oriented dialog system that uses human-human interaction data. The key aspe...