Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Parallel Mining of Association Rules
IEEE Transactions on Knowledge and Data Engineering
Scalable Algorithms for Association Mining
IEEE Transactions on Knowledge and Data Engineering
Pincer-Search: An Efficient Algorithm for Discovering the Maximum Frequent Set
IEEE Transactions on Knowledge and Data Engineering
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Data Mining and Knowledge Discovery in Databases: Implications for Scientific Databases
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
A New Data Clustering Approach for Data Mining in Large Databases
ISPAN '02 Proceedings of the 2002 International Symposium on Parallel Architectures, Algorithms and Networks
An efficient cluster and decomposition algorithm for mining association rules
Information Sciences—Informatics and Computer Science: An International Journal
Compression, Clustering, and Pattern Discovery in Very High-Dimensional Discrete-Attribute Data Sets
IEEE Transactions on Knowledge and Data Engineering
Computers & Mathematics with Applications
Application of ant K-means on clustering analysis
Computers & Mathematics with Applications
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fast self-organizing feature map algorithm
IEEE Transactions on Neural Networks
A new model of self-organizing neural networks and its application in data projection
IEEE Transactions on Neural Networks
Augmenting productivity analysis with data mining: An application on IT business value
Expert Systems with Applications: An International Journal
Mining the change of event trends for decision support in environmental scanning
Expert Systems with Applications: An International Journal
Methodological Review: Health GIS and HIV/AIDS studies: Perspective and retrospective
Journal of Biomedical Informatics
Discovering competitive intelligence by mining changes in patent trends
Expert Systems with Applications: An International Journal
Decision support for the maintenance management of green areas
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Application of particle swarm optimization to association rule mining
Applied Soft Computing
Locality sensitive hashing for sampling-based algorithms in association rule mining
Expert Systems with Applications: An International Journal
Using data mining technique to enhance tax evasion detection performance
Expert Systems with Applications: An International Journal
Discovering gene association networks by multi-objective evolutionary quantitative association rules
Journal of Computer and System Sciences
Multi-objective PSO algorithm for mining numerical association rules without a priori discretization
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
In addition to sharing and applying the knowledge in the community, knowledge discovery has become an important issue in the knowledge economic era. Data mining plays an important role of knowledge discovery. Therefore, this study intends to propose a novel framework of data mining which clusters the data first and then followed by association rules mining. The first stage employs the ant system-based clustering algorithm (ASCA) and ant K-means (AK) to cluster the database, while the ant colony system-based association rules mining algorithm is applied to discover the useful rules for each group. The medical database provided by the National Health Insurance Bureau of Taiwan Government is used to verify the proposed method. The evaluation results showed that the proposed method not only is able to extract the rules much faster, but also can discover more important rules.