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MB3-Miner: Efficient mining eMBedded subTREEs using tree model guided candidate generation

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Open access
Authors
Chang, Elizabeth
Tan, H.
Dillon, Tharam S.
Hadzic, Fedja
Feng, L.
Date
2005
Type
Conference Paper

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Citation
Chang, Elizabeth and Tan, Henry and Dillon, Tharam S. and Hadzic, Fedja and Feng, Ling. 2005. : MB3-Miner: Efficient mining eMBedded subTREEs using tree model guided candidate generation, in Ras, Z.W. and Tsumoto, S. and Zighed, D.A. (ed), First International Workshop on Mining Complex Data (MCD) in conjunction with ICDM'05, Nov 27 2005, pp. 103-110. Houston, Texas, USA: IEEE.
Source Title
Proceedings of the First International Workshop on Mining Complex Data (MCD)
Source Conference
First International Workshop on Mining Complex Data (MCD) in conjunction with ICDM'05
Faculty
Curtin Business School
School of Information Systems
School
Centre for Extended Enterprises and Business Intelligence
Remarks

Copyright 2005 IEEE

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Abstract

Tree mining has many useful applications in areas such as Bioinformatics, XML mining, Web mining, etc. In general, most of the formally represented information in these domains is a tree structured form. In this paper we focus on mining frequent embedded subtrees from databases of rooted labelled ordered subtrees. We propose a novel and unique embedding list representation that is suitable for describing embedded subtrees. This representation is completely different from the string-like or conventional adjacency list representation previously utilized for trees. We present the mathematical model of a breadth-first-search Tree Model Guided (TMG) candidate generation approach previously introduced in [8]. The key characteristic of the TMG approach is that it enumerates fewer candidates by ensuring that only valid candidates that conform to the structural aspects of the data are generated as opposed to the join approach. Our experiments with both synthetic and real-life datasets provide comparisons against one of the state-of-the-art algorithms, TreeMiner [15], and they demonstrate the effectiveness and the efficiency of the technique.