C4.5: programs for machine learning
C4.5: programs for machine learning
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
A survey of knowledge acquisition techniques and tools
Readings in knowledge acquisition and learning
Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Advances in knowledge discovery and data mining
Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Pruning and summarizing the discovered associations
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining the most interesting rules
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Generating non-redundant association rules
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Small is beautiful: discovering the minimal set of unexpected patterns
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-level organization and summarization of the discovered 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
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
A New SQL-like Operator for Mining Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Post-analysis of learned rules
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Experiences in building a tool for navigating association rule result sets
ACSW Frontiers '04 Proceedings of the second workshop on Australasian information security, Data Mining and Web Intelligence, and Software Internationalisation - Volume 32
A Framework for Evaluating Knowledge-Based Interestingness of Association Rules
Fuzzy Optimization and Decision Making
Pruning and Visualizing Generalized Association Rules in Parallel Coordinates
IEEE Transactions on Knowledge and Data Engineering
Knowledge Discovery with Genetic Programming for Providing Feedback to Courseware Authors
User Modeling and User-Adapted Interaction
Using Information-Theoretic Measures to Assess Association Rule Interestingness
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Clustering web images using association rules, interestingness measures, and hypergraph partitions
ICWE '06 Proceedings of the 6th international conference on Web engineering
Ranking discovered rules from data mining with multiple criteria by data envelopment analysis
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Interactive visual exploration of association rules with rule-focusing methodology
Knowledge and Information Systems
Evaluation of rule interestingness measures in medical knowledge discovery in databases
Artificial Intelligence in Medicine
Mining unexpected multidimensional rules
Proceedings of the ACM tenth international workshop on Data warehousing and OLAP
On discovery of soft associations with "most" fuzzy quantifier for item promotion applications
Information Sciences: an International Journal
Knowledge actionability: satisfying technical and business interestingness
International Journal of Business Intelligence and Data Mining
A method for mining quantitative association rules
SMO'06 Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization
Integrating in-process software defect prediction with association mining to discover defect pattern
Information and Software Technology
Domain-Driven Local Exceptional Pattern Mining for Detecting Stock Price Manipulation
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Interestingness filtering engine: Mining Bayesian networks for interesting patterns
Expert Systems with Applications: An International Journal
User Modeling and User-Adapted Interaction
A new method for ranking discovered rules from data mining by DEA
Expert Systems with Applications: An International Journal
Towards Business Interestingness in Actionable Knowledge Discovery
Proceedings of the 2008 conference on Applications of Data Mining in E-Business and Finance
A new method for ranking changes in customer's behavioral patterns in department stores
Proceedings of the 11th International Conference on Electronic Commerce
Intelligent assistance for teachers in collaborative e-learning environments
Computers & Education
Identifying interesting assertions from the web
Proceedings of the 18th ACM conference on Information and knowledge management
Using ontologies to facilitate post-processing of association rules by domain experts
Information Sciences: an International Journal
Domain-driven KDD for mining functionally novel rules and linking disjoint medical hypotheses
Knowledge-Based Systems
Investigation of rule interestingness in medical data mining
AM'03 Proceedings of the Second international conference on Active Mining
Spiral multi-aspect hepatitis data mining
AM'03 Proceedings of the Second international conference on Active Mining
Discovering interesting association rules by clustering
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
A unified approach for discovery of interesting association rules in medical databases
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
Using rules discovery for the continuous improvement of e-learning courses
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Actionable knowledge discovery and delivery
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
An approach for LMS assessment
International Journal of Technology Enhanced Learning
Association Rules Evaluation by a Hybrid Multiple Criteria Decision Method
International Journal of Knowledge and Systems Science
Mining numerical association rules via multi-objective genetic algorithms
Information Sciences: an International Journal
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Association rules are a class of important regularities in databases. They are found to be very useful in practical applications. However, association rule mining algorithms tend to produce a huge number of rules, most of which are of no interest to the user. Due to the large number of rules, it is very difficult for the user to analyze them manually to identify those truly interesting ones. This article presents a new approach to assist the user in finding interesting rules (in particular, unexpected rules) from a set of discovered association rules. This technique is characterized by analyzing the discovered association rules using the user's existing knowledge about the domain and then ranking the discovered rules according to various interestingness criteria, e.g., conformity and various types of unexpectedness. This technique has been implemented and successfully used in a number of applications.