Mining single pass weighted pattern tree

Authors:
Olivia Castelino;Preetham Kumar;Srivatsa Maddodi
Affiliations:
Department of Computer Science and Engineering, Nitte Mahalinga Adyanthaya Memorial Institute of Technology, An Autonomous Institution under Visveswaraiah Technological University, Belgaum, India;Department of Information and Communication Techonolgy, Manipal Institute of Technology, Manipal University, India;Department of Information and Communication Techonolgy, Manipal Institute of Technology, Manipal University, India
Venue:
ICDEM'10 Proceedings of the Second international conference on Data Engineering and Management
Year:
2010

Citing 6
Cited 0

Mining frequent patterns without candidate generation

SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Scalable, Distributed and Dynamic Mining of Association Rules

HiPC '00 Proceedings of the 7th International Conference on High Performance Computing
Similarity search of time-warped subsequences via a suffix tree

Information Systems
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach

Data Mining and Knowledge Discovery
Efficient mining of weighted interesting patterns with a strong weight and/or support affinity

Information Sciences: an International Journal
CP-tree: a tree structure for single-pass frequent pattern mining

PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

Weighted tree mining has become an important research topic in Data mining. There are several algorithms for mining Frequent Pattern trees. FP growth algorithm using FP tree has been considered for frequent pattern mining because of its enormous performance and development compared to the candidate generation model of Apriori. The purpose of our work is to provide a tree structure for incremental and interactive weighted pattern mining by only one database scan. It is applied to existing Compact pattern (CP) tree. CP tree dynamically achieves frequency-descending prefix tree structure with a single-pass by applying tree restructuring technique and considerably reducing the mining time. It is competent of using prior tree structures and acquires mining outcomes to decrease the computation by incredible amount. Performance analysis show that our tree structure is very efficient for incremental and interactive weighted pattern mining.