Explora: a multipattern and multistrategy discovery assistant
Advances in knowledge discovery and data mining
Fast discovery of association rules
Advances in knowledge discovery and data mining
Pruning and summarizing the discovered associations
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
An Information Theoretic Approach to Rule Induction from Databases
IEEE Transactions on Knowledge and Data Engineering
What Makes Patterns Interesting in Knowledge Discovery Systems
IEEE Transactions on Knowledge and Data Engineering
Finding Interesting Patterns Using User Expectations
IEEE Transactions on Knowledge and Data Engineering
Discovery of Surprising Exception Rules Based on Intensity of Implication
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
Unified Algorithm for Undirected Discovery of Execption Rules
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Fast Discovery of Interesting Rules
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Evaluating Hypothesis-Driven Exception-Rule Discovery with Medical Data Sets
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Exception Rule Mining with a Relative Interestingness Measure
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Scheduled Discovery of Exception Rules
DS '99 Proceedings of the Second International Conference on Discovery Science
Unified algorithm for undirected discovery of exception rules: Research Articles
International Journal of Intelligent Systems - Knowledge Discovery: Dedicated to Jan M. Żytkow
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In this paper, we give an interpretation of our undirected exception rule discovery as local pattern detection and introduce some of our endeavors. Our undirected exception rule discovery outputs a set of rule pairs, each of which represents a pair of strong rule and its exception rule. A local pattern is defined as a pattern which deviates from a global model, and can be considered to correspond to our exception rule if the global model corresponds to our strong rule. Several attempts for undirected exception rule discovery are introduced in the context of local pattern detection. Our results mainly concern interestingness measure, algorithmic issues, noise modeling, and performance evaluation.