Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Mining fuzzy association rules in databases
ACM SIGMOD Record
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Efficient Mining of Intertransaction Association Rules
IEEE Transactions on Knowledge and Data Engineering
Synthesizing High-Frequency Rules from Different Data Sources
IEEE Transactions on Knowledge and Data Engineering
Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
A Super-Programming Approach for Mining Association Rules in Parallel on PC Clusters
IEEE Transactions on Parallel and Distributed Systems
Compression, Clustering, and Pattern Discovery in Very High-Dimensional Discrete-Attribute Data Sets
IEEE Transactions on Knowledge and Data Engineering
Mining block correlations to improve storage performance
ACM Transactions on Storage (TOS)
Distributed approximate mining of frequent patterns
Proceedings of the 2005 ACM symposium on Applied computing
Mining Version Histories to Guide Software Changes
IEEE Transactions on Software Engineering
Fast Algorithms for Frequent Itemset Mining Using FP-Trees
IEEE Transactions on Knowledge and Data Engineering
A User-guided Association Rules Mining Method and Its Application
CIT '05 Proceedings of the The Fifth International Conference on Computer and Information Technology
Software Defect Association Mining and Defect Correction Effort Prediction
IEEE Transactions on Software Engineering
ACM SIGKDD Explorations Newsletter
Aggregation of orders in distribution centers using data mining
Expert Systems with Applications: An International Journal
An efficient data mining approach for discovering interesting knowledge from customer transactions
Expert Systems with Applications: An International Journal
A Kansei mining system for affective design
Expert Systems with Applications: An International Journal
Mining association rules with multiple minimum supports using maximum constraints
International Journal of Approximate Reasoning
Mining association rules with multi-dimensional constraints
Journal of Systems and Software
CBAR: an efficient method for mining association rules
Knowledge-Based Systems
Association rule mining: models and algorithms
Association rule mining: models and algorithms
IEEE Transactions on Information Technology in Biomedicine
EEG Transient Event Detection and Classification Using Association Rules
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy versus quantitative association rules: a fair data-driven comparison
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A proximate dynamics model for data mining
Expert Systems with Applications: An International Journal
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Although bundled commodities are largely existed in supermarket, there are few investigations about bundled commodities mining. In this study, interval-valued association rules as a novel and possible approach to solving the bundled commodities mining issue, is proposed. Properties research based on interval-valued association rules is conducted, and an interval-valued rule pattern: is constructed, where F denotes set of interval-valued ruses, @? and @? denote the disjunctive operation and conjunctive operation, respectively. Furthermore, one of the properties satisfied by the interval-valued rules: A@?C=B@?C and A@?C=B@?C@?A=B, where A, B, C are there different rules, is validated and utilized to mine the bundled commodities. Finally, a large-scale software engineering project relative to interval-valued rule mining is implemented to merge flight testing information about aircrafts which validates the technique of mining bundled commodities can be discovered a special relation between objects. These initial investigations provide a researchable framework for bundled commodities mining.