Introduction to Grey system theory
The Journal of Grey System
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
CURE: an efficient clustering algorithm for large databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Journal of the ACM (JACM)
Synthesizing High-Frequency Rules from Different Data Sources
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh 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
Knowledge Discovery in Multiple Databases
Knowledge Discovery in Multiple Databases
Efficient mining of both positive and negative association rules
ACM Transactions on Information Systems (TOIS)
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
A logical framework for identifying quality knowledge from different data sources
Decision Support Systems
Context-based market basket analysis in a multiple-store environment
Decision Support Systems
Designing online selling mechanisms: Transparency levels and prices
Decision Support Systems
Design concept evaluation in product development using rough sets and grey relation analysis
Expert Systems with Applications: An International Journal
Finding "persistent rules": Combining association and classification results
Expert Systems with Applications: An International Journal
Mining globally interesting patterns from multiple databases using kernel estimation
Expert Systems with Applications: An International Journal
Measuring influence of an item in a database over time
Pattern Recognition Letters
Association patterns for data modeling and definition
Knowledge and Information Systems
Methods for mining frequent items in data streams: an overview
Knowledge and Information Systems
CLAP: Collaborative pattern mining for distributed information systems
Decision Support Systems
A dynamic decision support system to predict the value of customer for new product development
Decision Support Systems
Merging local patterns using an evolutionary approach
Knowledge and Information Systems
Mining top−k frequent patterns without minimum support threshold
Knowledge and Information Systems
The benefit of information asymmetry: When to sell to informed customers?
Decision Support Systems
A unified view of the apriori-based algorithms for frequent episode discovery
Knowledge and Information Systems
Mining temporal patterns in popularity of web items
Information Sciences: an International Journal
Mining actionable behavioral rules
Decision Support Systems
Quality of information-based source assessment and selection
Neurocomputing
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Many kinds of patterns (e.g., association rules, negative association rules, sequential patterns, and temporal patterns) have been studied for various applications, but very little work has been reported on multiple correlated databases that are all relevant. This paper proposes an efficient method for mining stable patterns from multiple correlated databases. First, we define the notion of stable items according to two constraint conditions, minsupp and varivalue. We then measure the similarity between stable items based on gray relational analysis, and present a hierarchical gray clustering method for mining stable patterns consisting of stable items. Finally, experiments are conducted on four datasets, and the results of the experiments show that our method is useful and efficient.