Fuzzy sets, decision making and expert systems
Fuzzy sets, decision making and expert systems
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Why triangular membership functions?
Fuzzy Sets and Systems
Applied multivariate techniques
Applied multivariate techniques
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Fast discovery of association rules
Advances in knowledge discovery and data mining
Web usage mining for Web site evaluation
Communications of the ACM
Data mining: concepts and techniques
Data mining: concepts and techniques
Numerical analysis of the learning of fuzzified neural networks from fuzzy if—then rules
Fuzzy Sets and Systems - Special issue on clustering and learning
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Three objective genetics-based machine learning for linguisitc rule extraction
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Mining fuzzy association rules for classification problems
Computers and Industrial Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Fuzzy Data Mining: Effect of Fuzzy Discretization
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fuzzy query translation for relational database systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Generating learning sequences for decision makers through data mining and competence set expansion
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Fuzzy Systems
Selecting fuzzy if-then rules for classification problems using genetic algorithms
IEEE Transactions on Fuzzy Systems
Recognizing unexpected recurrence behaviors with fuzzy measures in sequence databases
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
A change detection method for sequential patterns
Decision Support Systems
Analysis on repeat-buying patterns
Knowledge-Based Systems
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Sequential patterns refer to the frequently occurring patterns related to time or other sequences, and have been widely applied to solving decision problems. For example, they can help managers determine which items were bought after some items had been bought. However, since fuzzy sequential patterns described by natural language are one type of fuzzy knowledge representation, they are helpful in building a prototype fuzzy knowledge base in a business. Moreover, each fuzzy sequential pattern consisting of several fuzzy sets described by the natural language is well suited for the thinking of human subjects and will help to increase the flexibility for users in making decisions. Additionally, since the comprehensibility of fuzzy representation by human users is a criterion in designing a fuzzy system, the simple fuzzy partition method is preferable. In this method, each attribute is partitioned by its various fuzzy sets with pre-specified membership functions. The advantage of the simple fuzzy partition method is that the linguistic interpretation of each fuzzy set is easily obtained. The main aim of this paper is exactly to propose a fuzzy data mining technique to discover fuzzy sequential patterns by using the simple partition method. Two numerical examples are utilized to demonstrate the usefulness of the proposed method.