Using a projection-based approach to mine frequent inter-transaction patterns

Authors:
Chun-Sheng Wang;Kuo-Chung Chu
Affiliations:
Department of Information Management, Jinwen University of Science and Technology, No. 99, An-Chung Road, Hsin-Tien, Dist. New Taipei City, Taiwan, ROC;Department of Information Management, National Taipei University of Nursing and Health Sciences, No. 365, Min-Te Road, Taipei, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 12
Cited 1

Beyond intratransaction association analysis: mining multidimensional intertransaction association rules

ACM Transactions on Information Systems (TOIS)
A tree projection algorithm for generation of frequent item sets

Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
Inter-transactional association rules for multi-dimensional contexts for prediction and their application to studying meterological data

Data & Knowledge Engineering
Efficient Mining of Intertransaction Association Rules

IEEE Transactions on Knowledge and Data Engineering
A template model for multidimensional inter-transactional association rules

The VLDB Journal — The International Journal on Very Large Data Bases
Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach

IEEE Transactions on Knowledge and Data Engineering
Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques
Mining spatial association rules in image databases

Information Sciences: an International Journal
An efficient algorithm for mining frequent inter-transaction patterns

Information Sciences: an International Journal
Mining inter-sequence patterns

Expert Systems with Applications: An International Journal
From intra-transaction to generalized inter-transaction: Landscaping multidimensional contexts in association rule mining

Information Sciences: an International Journal
Mining association rules with multi-dimensional constraints

Journal of Systems and Software

Mining generalized temporal patterns based on fuzzy counting

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	12.05

Visualization

Abstract

In this paper, we propose an algorithm called PITP-Miner that utilizes a projection based approach to mine frequent inter-transaction patterns efficiently. The algorithm only searches for local frequent items in a projected database that stores potential local inter-transaction items and partitions the database into a set of smaller databases recursively. In addition, two pruning strategies are designed to further condense the partitioned databases and thus accelerate the algorithm. Our experiment results demonstrate that the proposed PITP-Miner algorithm outperforms the ITP-Miner and FITI algorithms in most cases.