Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
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
Discover Risky Active Faults by Indexing an Earthquake Sequence
DS '99 Proceedings of the Second International Conference on Discovery Science
Applying KeyGraph and Data Crystallization to technology monitoring on solar cell
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Knowledge integration and management in autonomous systems
Finding top-N chance patterns with KeyGraph®-based importance
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
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Chance discovery is to notice and explain the significance of a chance, especially if the chance is rare and its significance is unnoticed. Chance discovery is essential for various real requirements in human life. The paper presents the significance and the achieved methods of chance discovery. Fundamental discussions of how to realize chance discovery extracts keys for the progress of chance discovery: communication, imagination, and data mining. As an approach to chance discovery, visualized data mining methods are shown as tools aiding chance discoveries.