Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
An effective hash-based algorithm for mining association rules
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Association rules over interval data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Algorithms for association rule mining — a general survey and comparison
ACM SIGKDD Explorations Newsletter
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Mining optimized support rules for numeric attributes
Information Systems
Data Mining and Machine Oriented Modeling: A Granular Computing Approach
Applied Intelligence
Mining association rules using inverted hashing and pruning
Information Processing Letters
Efficient Mining of Association Rules in Distributed Databases
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
Discovery of Multiple-Level Association Rules from Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Mining inter-organizational retailing knowledge for an alliance formed by competitive firms
Information and Management
Mining association rules on significant rare data using relative support
Journal of Systems and Software
Fuzzy data mining for interesting generalized association rules
Fuzzy Sets and Systems - Theme: Learning and modeling
Mining Web Pages for Data Records
IEEE Intelligent Systems
Database classification for multi-database mining
Information Systems
Algorithms for mining association rules in bag databases
Information Sciences—Informatics and Computer Science: An International Journal
Microarray gene expression data association rules mining based on BSC-tree and FIS-tree
Data & Knowledge Engineering - Special issue: Biological data management
IEEE Transactions on Knowledge and Data Engineering
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Market basket analysis in a multiple store environment
Decision Support Systems
A study of applying data mining to early intervention for developmentally-delayed children
Expert Systems with Applications: An International Journal
A new approach for discovering fuzzy quantitative sequential patterns in sequence databases
Fuzzy Sets and Systems
A sampling-based method for mining frequent patterns from databases
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Discovering fuzzy time-interval sequential patterns in sequence databases
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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
Mining fuzzy association rules from questionnaire data
Knowledge-Based Systems
A neural-fuzzy modelling framework based on granular computing: Concepts and applications
Fuzzy Sets and Systems
Mining fuzzy association rules from uncertain data
Knowledge and Information Systems
Application rough sets theory to ordinal scale data for discovering knowledge
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Mining fuzzy specific rare itemsets for education data
Knowledge-Based Systems
Extracting compact and information lossless sets of fuzzy association rules
Fuzzy Sets and Systems
Function and service pattern analysis for facilitating the reconfiguration of collaboration systems
Computers and Industrial Engineering
Relative association rules based on rough set theory
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Discovering frequent itemsets on uncertain data: a systematic review
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
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Categorical data can generally be classified into ordinal data and nominal data. Although there have been numerous studies on finding association rules from nominal data, few have tried to do so from ordinal data. Additionally, previous mining algorithms usually assume that the input data is precise and clean, which is unrealistic in practical situations. Real-world data tends to be imprecise due to human errors, instrument errors, recording errors, and so on. Therefore, this paper proposes a new approach to discovering association rules from imprecise ordinal data. Experimental results from the survey data show the feasibility of the proposed mining algorithm. Performance analyses of the algorithms also show that the proposed approach can discover interesting and valuable rules that could never be found using the conventional approach, the Apriori algorithm.