Paper Info
Title
Frequent Subtree Mining - An Overview
Abstract
Mining frequent subtrees from databases of labeled trees is a new research field that has many practical applications in areas such as computer networks, Web mining, bioinformatics, XML document mining, etc. These applications share a requirement for the more expressive power of labeled trees to capture the complex relations among data entities. Although frequent subtree mining is a more difficult task than frequent itemset mining, most existing frequent subtree mining algorithms borrow techniques from the relatively mature association rule mining area. This paper provides an overview of a broad range of tree mining algorithms. We focus on the common theoretical foundations of the current frequent subtree mining algorithms and their relationship with their counterparts in frequent itemset mining. When comparing the algorithms, we categorize them according to their problem definitions and the techniques employed for solving various subtasks of the subtree mining problem. In addition, we also present a thorough performance study for a representative family of algorithms.
Year
Venue
Keywords
2005
Fundam. Inform.
subtree mining problem,frequent itemset mining,mature association rule mining,frequent subtrees,frequent subtree mining,web mining,tree mining algorithm,a priori,subtree isomorphism,enumeration tree,canonical representation,existing frequent subtree mining,xml document mining,current frequent subtree mining,computer network,association rule mining,xml document,expressive power
Field
DocType
Volume
Data mining,Data stream mining,Concept mining,Web mining,XML,Computer science,Molecule mining,Tree (data structure),Frequent subtree mining,Association rule learning
Journal
66
Issue
Citations 
PageRank 
1-2
140
4.49
References 
Authors
35
4
Search Limit
100140
Name
Order
Citations
PageRank
Yun Chi168729.90
R. R. Muntz249091558.80
Siegfried Nijssen3110359.13
Joost N. Kok41429121.49