Inter-company comparison using modified TOPSIS with objective weights
Computers and Operations Research
What Makes Patterns Interesting in Knowledge Discovery Systems
IEEE Transactions on Knowledge and Data Engineering
Analyzing the Subjective Interestingness of Association Rules
IEEE Intelligent Systems
Selecting the right objective measure for association analysis
Information Systems - Knowledge discovery and data mining (KDD 2002)
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Interestingness measures for data mining: A survey
ACM Computing Surveys (CSUR)
Ranking discovered rules from data mining with multiple criteria by data envelopment analysis
Expert Systems with Applications: An International Journal
Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment
Expert Systems with Applications: An International Journal
Incorporating Background Knowledge for Subjective Rule Evaluation
ICTAI '07 Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence - Volume 02
Interestingness filtering engine: Mining Bayesian networks for interesting patterns
Expert Systems with Applications: An International Journal
A new method for ranking discovered rules from data mining by DEA
Expert Systems with Applications: An International Journal
Prioritization of association rules in data mining: Multiple criteria decision approach
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
Various rules can be generated from databases by using association rule algorithms, but only a small number of these rules may be selected for implementation due to the limitations of resources. Accordingly, evaluating the quality of these rules becomes a hot topic in the data mining field. Based on multiple criteria decision theory, a framework for evaluating the mined association rules using TOPSIS method with combination weights is proposed, which takes into account both objective interestingness measures and the users' domain information. An example of market basket analysis is applied to illustrate the applicability of this method.