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» Phenomenal Data Mining: From Data to Phenomena
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TSE
2008
113views more  TSE 2008»
15 years 6 months ago
Discovering Neglected Conditions in Software by Mining Dependence Graphs
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...
Ray-Yaung Chang, Andy Podgurski, Jiong Yang
SAC
2009
ACM
16 years 1 months ago
Combining statistics and semantics via ensemble model for document clustering
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
ICDM
2005
IEEE
185views Data Mining» more  ICDM 2005»
16 years 8 days ago
Semi-Supervised Mixture of Kernels via LPBoost Methods
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...
Jinbo Bi, Glenn Fung, Murat Dundar, R. Bharat Rao
ICDM
2003
IEEE
104views Data Mining» more  ICDM 2003»
15 years 12 months ago
Structure Search and Stability Enhancement of Bayesian Networks
Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
Hanchuan Peng, Chris H. Q. Ding
EMNLP
2008
15 years 8 months ago
Acquiring Domain-Specific Dialog Information from Task-Oriented Human-Human Interaction through an Unsupervised Learning
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...
Ananlada Chotimongkol, Alexander I. Rudnicky