Growing decision trees on support-less association rules
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
What Makes Patterns Interesting in Knowledge Discovery Systems
IEEE Transactions on Knowledge and Data Engineering
Combination of multiple classifiers for the customer's purchase behavior prediction
Decision Support Systems - Special issue: Agents and e-commerce business models
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Action-Rules: How to Increase Profit of a Company
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A Lazy Approach to Pruning Classification Rules
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Mining Case Bases for Action Recommendation
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Mining Optimal Actions for Profitable CRM
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Postprocessing Decision Trees to Extract Actionable Knowledge
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
On support thresholds in associative classification
Proceedings of the 2004 ACM symposium on Applied computing
An associative classifier based on positive and negative rules
Proceedings of the 9th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Action rules mining: Research Articles
International Journal of Intelligent Systems - Knowledge Discovery: Dedicated to Jan M. Żytkow
Mining for Interesting Action Rules
IAT '05 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
CARA: A Cultural-Reasoning Architecture
IEEE Intelligent Systems
Annals of Mathematics and Artificial Intelligence
Tree-based Construction of Low-cost Action Rules
Fundamenta Informaticae
Action Rules Discovery without Pre-existing Classification Rules
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
ICDMW '08 Proceedings of the 2008 IEEE International Conference on Data Mining Workshops
Mining action rules from scratch
Expert Systems with Applications: An International Journal
Flexible Frameworks for Actionable Knowledge Discovery
IEEE Transactions on Knowledge and Data Engineering
Mining stable patterns in multiple correlated databases
Decision Support Systems
CBC: An associative classifier with a small number of rules
Decision Support Systems
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Many applications can benefit from constructing models to predict the behavior of an entity. However, such models do not provide the user with explicit knowledge that can be directly used to influence (restrain or encourage) behavior for the user's interest. Undoubtedly, the user often exactly needs such knowledge. This type of knowledge is called actionable knowledge. Actionability is a very important criterion measuring the interestingness of mined patterns. In this paper, to mine such knowledge, we take a first step toward formally defining a new class of data mining problem, named actionable behavioral rule mining. Our definition explicitly states the problem as a search problem in a framework of support and expected utility. We also propose two algorithms for mining such rules. Our experiment shows the validity of our approach, as well as the practical value of our defined problem.