Paper Info
Title
An Efficient Approach for Mining Frequent Patterns Based on Traversing a Frequent Pattern Tree
Abstract
Mining frequent patterns is an important task for knowledge discovery, which discovers the groups of items appearing always together excess of a user specified threshold. A famous algorithm for mining frequent patterns is FP-Growth which constructs a structure called FP-tree and recursively mines frequent patterns from this structure by building conditional FP-trees. However, It is costly to recursively construct conditional FP-trees. In order to decrease the usage of memory space and speed up the mining process, we propose an efficient approach for mining frequent patterns. Our approach only needs to construct a FP-tree and traverse each subtree of the FP-tree to generate all the frequent patterns for an item without constructing any other subtrees. Since there is no extra trees constructed and only a subtree needs to be traversed to generate frequent patterns for an item, our approach is much more efficient than FP-Growth algorithm. The experimental results also show that our approach significantly outperforms FP-Growth algorithm.
Year
DOI
Venue
2008
10.1109/CSSE.2008.801
CSSE (4)
Keywords
Field
DocType
extra tree,conditional fp-trees,recursively mine,mining process,knowledge discovery,frequent pattern tree,efficient approach,mining frequent patterns,important task,fp-growth algorithm,frequent pattern mining,data mining,famous algorithm,frequent pattern,transaction database,fp-trees,fp-growth,databases,argon,merging,integrated circuits,pediatrics
Data mining,Computer science,Tree (data structure),Knowledge extraction,Merge (version control),Database,Recursion,Speedup,Traverse
Conference
Volume
ISBN
Citations 
4
978-0-7695-3336-0
0
PageRank 
References 
Authors
0.34
4
4
Name
Order
Citations
PageRank
Show-Jane Yen1537130.05
Yue-Shi Lee254341.14
Chiu-Kuang Wang3293.10
Jung-Wei Wu4110.98