Fuzzy sets, decision making and expert systems
Fuzzy sets, decision making and expert systems
Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
A fuzzy Prolog database system
A fuzzy Prolog database system
Uncertainty and vagueness in knowledge based systems
Uncertainty and vagueness in knowledge based systems
C4.5: programs for machine learning
C4.5: programs for machine learning
Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Expert Systems: Design and Development
Expert Systems: Design and Development
Expert Systems: Principles and Programming
Expert Systems: Principles and Programming
What Makes Patterns Interesting in Knowledge Discovery Systems
IEEE Transactions on Knowledge and Data Engineering
Data-Driven Discovery of Quantitative Rules in Relational Databases
IEEE Transactions on Knowledge and Data Engineering
Systems for Knowledge Discovery in Databases
IEEE Transactions on Knowledge and Data Engineering
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
Abstract-Driven Pattern Discovery in Databases
IEEE Transactions on Knowledge and Data Engineering
Post-analysis of learned rules
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Evaluating the novelty of text-mined rules using lexical knowledge
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Detecting Group Differences: Mining Contrast Sets
Data Mining and Knowledge Discovery
Efficient Mining of Niches and Set Routines
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
In Pursuit of Interesting Patterns with Undirected Discovery of Exception Rules
Progress in Discovery Science, Final Report of the Japanese Discovery Science Project
Domain knowledge to support the discovery process: previously discovered knowledge
Handbook of data mining and knowledge discovery
Domain knowledge to support the discovery process: user preferences
Handbook of data mining and knowledge discovery
Postprocessing Decision Trees to Extract Actionable Knowledge
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
An iterative hypothesis-testing strategy for pattern discovery
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
A Framework for Evaluating Knowledge-Based Interestingness of Association Rules
Fuzzy Optimization and Decision Making
Interestingness measures for data mining: A survey
ACM Computing Surveys (CSUR)
Rule interestingness analysis using OLAP operations
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Identifying bridging rules between conceptual clusters
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Opportunity map: identifying causes of failure - a deployed data mining system
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting Actionable Knowledge from Decision Trees
IEEE Transactions on Knowledge and Data Engineering
Improving discriminative sequential learning by discovering important association of statistics
ACM Transactions on Asian Language Information Processing (TALIP)
A parallel genetic algorithm approach for automated discovery of censored production rules
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
AISIID: An artificial immune system for interesting information discovery on the web
Applied Soft Computing
On discovery of soft associations with "most" fuzzy quantifier for item promotion applications
Information Sciences: an International Journal
DDDM2007: Domain Driven Data Mining
ACM SIGKDD Explorations Newsletter - Special issue on visual analytics
Mining class-bridge rules based on rough sets
Expert Systems with Applications: An International Journal
Discovering unexpected documents in corpora
Knowledge-Based Systems
Compression-Based Measures for Mining Interesting Rules
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
A new method for ranking changes in customer's behavioral patterns in department stores
Proceedings of the 11th International Conference on Electronic Commerce
A comprehensive survey of numeric and symbolic outlier mining techniques
Intelligent Data Analysis
Mining changes in customer behavior in retail marketing
Expert Systems with Applications: An International Journal
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Knowledge extraction using a conceptual information system (ExCIS)
ODBIS'05/06 Proceedings of the First and Second VLDB conference on Ontologies-based databases and information systems
Efficient prime-based method for interactive mining of frequent patterns
Expert Systems with Applications: An International Journal
A novel evolutionary method to search interesting association rules by keywords
Expert Systems with Applications: An International Journal
Conceptual distance for association rules post-processing
MEDI'11 Proceedings of the First international conference on Model and data engineering
Interesting patterns extraction using prior knowledge
DS'06 Proceedings of the 9th international conference on Discovery Science
Evaluating interestingness measures with linear correlation graph
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Mining bridging rules between conceptual clusters
Applied Intelligence
Undirected exception rule discovery as local pattern detection
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
A data analysis approach for evaluating the behavior of interestingness measures
DS'05 Proceedings of the 8th international conference on Discovery Science
Iterative bayesian network implementation by using annotated association rules
EKAW'06 Proceedings of the 15th international conference on Managing Knowledge in a World of Networks
Searching interesting association rules based on evolutionary computation
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Knowledge discovery interestingness measures based on unexpectedness
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Evolutionary and immune algorithms applied to association rule mining
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Confirmation measures of association rule interestingness
Knowledge-Based Systems
Discovering diverse-frequent patterns in transactional databases
Proceedings of the 17th International Conference on Management of Data
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One of the major problems in the field of knowledge discovery (or data mining) is the interestingness problem. Past research and applications have found that, in practice, it is all too easy to discover a huge number of patterns in a database. Most of these patterns are actually useless or uninteresting to the user. But due to the huge number of patterns, it is difficult for the user to comprehend them and to identify those interesting to him/her. To prevent the user from being overwhelmed by the large number of patterns, techniques are needed to rank them according to their interestingness. In this paper, we propose such a technique, called the user-expectation method. In this technique, the user is first asked to provide his/her expected patterns according to his/her past knowledge or intuitive feelings. Given these expectations, the system uses a fuzzy matching technique to match the discovered patterns against the user's expectations, and then rank the discovered patterns according to the matching results. A variety of rankings can be performed for different purposes, such as to confirm the user's knowledge and to identify unexpected patterns, which are by definition interesting. The proposed technique is general and interactive.