Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Mining association rules with multiple minimum supports
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Multiple-Level Association Rules in Large Databases
IEEE Transactions on Knowledge and Data Engineering
Alternative Interest Measures for Mining Associations in Databases
IEEE Transactions on Knowledge and Data Engineering
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th International Conference on Data Engineering
Mining Mutually Dependent Patterns
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Top Down FP-Growth for Association Rule Mining
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Selecting the right interestingness measure for association patterns
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
DualMiner: a dual-pruning algorithm for itemsets with constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent item sets by opportunistic projection
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Efficient Mining of Constrained Correlated Sets
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Mining Association Rules with Weighted Items
IDEAS '98 Proceedings of the 1998 International Symposium on Database Engineering & Applications
CoMine: Efficient Mining of Correlated Patterns
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Mining Strong Affinity Association Patterns in Data Sets with Skewed Support Distribution
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
CLOSET+: searching for the best strategies for mining frequent closed itemsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Weighted Association Rule Mining using weighted support and significance framework
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
WAR: Weighted Association Rules for Item Intensities
Knowledge and Information Systems
Efficient closed pattern mining in the presence of tough block constraints
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Generalizing the notion of support
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Frequent Itemsets without Support Threshold: With and without Item Constraints
IEEE Transactions on Knowledge and Data Engineering
Interactive sequence discovery by incremental mining
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Algorithms for mining association rules in bag databases
Information Sciences—Informatics and Computer Science: An International Journal
TFP: An Efficient Algorithm for Mining Top-K Frequent Closed Itemsets
IEEE Transactions on Knowledge and Data Engineering
Mining maximal hyperclique pattern: A hybrid search strategy
Information Sciences: an International Journal
Mining lossless closed frequent patterns with weight constraints
Knowledge-Based Systems
Looking into the seeds of time: Discovering temporal patterns in large transaction sets
Information Sciences: an International Journal
Mining association rules with multi-dimensional constraints
Journal of Systems and Software
Pushing tougher constraints in frequent pattern mining
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
WLPMiner: weighted frequent pattern mining with length-decreasing support constraints
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Flexible online association rule mining based on multidimensional pattern relations
Information Sciences: an International Journal
A false negative approach to mining frequent itemsets from high speed transactional data streams
Information Sciences: an International Journal
Incremental and interactive mining of web traversal patterns
Information Sciences: an International Journal
Developing recommender systems with the consideration of product profitability for sellers
Information Sciences: an International Journal
A new framework for detecting weighted sequential patterns in large sequence databases
Knowledge-Based Systems
Mining Weighted Frequent Patterns Using Adaptive Weights
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Efficient Single-Pass Mining of Weighted Interesting Patterns
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Mining Weighted Frequent Patterns in Incremental Databases
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Top-down mining of frequent closed patterns from very high dimensional data
Information Sciences: an International Journal
Mining high utility patterns in incremental databases
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
Handling Dynamic Weights in Weighted Frequent Pattern Mining
IEICE - Transactions on Information and Systems
Mining frequent trajectory patterns in spatial-temporal databases
Information Sciences: an International Journal
Association rules mining with relative weighted support
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
Information Sciences: an International Journal
Approximate weighted frequent pattern mining with/without noisy environments
Knowledge-Based Systems
HUC-Prune: an efficient candidate pruning technique to mine high utility patterns
Applied Intelligence
Single-pass incremental and interactive mining for weighted frequent patterns
Expert Systems with Applications: An International Journal
Mining single pass weighted pattern tree
ICDEM'10 Proceedings of the Second international conference on Data Engineering and Management
Efficient mining of frequent items coupled with weight and /or support over progressive databases
ICDEM'10 Proceedings of the Second international conference on Data Engineering and Management
An efficient mining algorithm for maximal weighted frequent patterns in transactional databases
Knowledge-Based Systems
Interactive mining of high utility patterns over data streams
Expert Systems with Applications: An International Journal
Weighted association rule mining via a graph based connectivity model
Information Sciences: an International Journal
Efficient mining of maximal correlated weight frequent patterns
Intelligent Data Analysis
| Hi-index | 0.07 |
Most algorithms for frequent pattern mining use a support constraint to prune the combinatorial search space but support-based pruning is not enough. After mining datasets to obtain frequent patterns, the resulting patterns can have weak affinity. Although the minimum support can be increased, it is not effective for finding correlated patterns with increased weight and/or support affinity. Interesting measures have been proposed to detect correlated patterns but any approach does not consider both support and weight. In this paper, we present a new strategy, Weighted interesting pattern mining (WIP) in which a new measure, weight-confidence, is suggested to mine correlated patterns with the weight affinity. A weight range is used to decide weight boundaries and an h-confidence serves to identify support affinity patterns. In WIP, without additional computation cost, original h-confidence is used instead of the upper bound of h-confidence for performance improvement. WIP not only gives a balance between the two measures of weight and support, but also considers weight affinity and/or support affinity between items within patterns so more correlated patterns can be detected. To our knowledge, ours is the first work specifically to consider weight affinity between items of patterns. A comprehensive performance study shows that WIP is efficient and scalable for finding affinity patterns. Moreover, it generates fewer but more valuable patterns with the correlation. To decrease the number of thresholds, w-confidence, h-confidence and weighted support can be used selectively according to requirement of applications.