IMB3-Miner: Mining induced/embedded subtrees by constraining the level of embedding

Tree mining has recently attracted a lot of interest in areas such as Bioinformatics, XML mining, Web mining, etc. We are mainly concerned with mining frequent induced and embedded subtrees. While more interesting patterns can be obtained when mining embedded subtrees, unfortunately mining such embe...

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Bibliographic Details
Main Authors: Tan, H., Dillon, Tharam S., Hadzic, Fedja, Chang, Elizabeth, Feng, L.
Other Authors: Ng, W.K.
Format: Conference Paper
Published: Springer-Verlag 2006
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/41293
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author Tan, H.
Dillon, Tharam S.
Hadzic, Fedja
Chang, Elizabeth
Feng, L.
author2 Ng, W.K.
author_facet Ng, W.K.
Tan, H.
Dillon, Tharam S.
Hadzic, Fedja
Chang, Elizabeth
Feng, L.
author_sort Tan, H.
building Curtin Institutional Repository
collection Online Access
description Tree mining has recently attracted a lot of interest in areas such as Bioinformatics, XML mining, Web mining, etc. We are mainly concerned with mining frequent induced and embedded subtrees. While more interesting patterns can be obtained when mining embedded subtrees, unfortunately mining such embedding relationships can be very costly. In this paper, we propose an efficient approach to tackle the complexity of mining embedded subtrees by utilizing a novel Embedding List representation, Tree Model Guided enumeration, and introducing the Level of Embedding constraint. Thus, when it is too costly to mine all frequent embedded subtrees, one can decrease the level of embedding constraint gradually up to 1, from which all the obtained frequent subtrees are induced subtrees. Our experiments with both synthetic and real datasets against two known algorithms for mining induced and embedded subtrees, FREQT and TreeMiner, demonstrate the effectiveness and the efficiency of the technique.
first_indexed 2025-11-14T09:06:54Z
format Conference Paper
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T09:06:54Z
publishDate 2006
publisher Springer-Verlag
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-412932023-02-27T07:34:29Z IMB3-Miner: Mining induced/embedded subtrees by constraining the level of embedding Tan, H. Dillon, Tharam S. Hadzic, Fedja Chang, Elizabeth Feng, L. Ng, W.K. Kitsuregawa, M. Li, J. mining IMB3-Miner XML mining subtrees bioinformatics embedding embedded embed treeminger Tree mining has recently attracted a lot of interest in areas such as Bioinformatics, XML mining, Web mining, etc. We are mainly concerned with mining frequent induced and embedded subtrees. While more interesting patterns can be obtained when mining embedded subtrees, unfortunately mining such embedding relationships can be very costly. In this paper, we propose an efficient approach to tackle the complexity of mining embedded subtrees by utilizing a novel Embedding List representation, Tree Model Guided enumeration, and introducing the Level of Embedding constraint. Thus, when it is too costly to mine all frequent embedded subtrees, one can decrease the level of embedding constraint gradually up to 1, from which all the obtained frequent subtrees are induced subtrees. Our experiments with both synthetic and real datasets against two known algorithms for mining induced and embedded subtrees, FREQT and TreeMiner, demonstrate the effectiveness and the efficiency of the technique. 2006 Conference Paper http://hdl.handle.net/20.500.11937/41293 10.1007/11731139_52 Springer-Verlag restricted
spellingShingle mining
IMB3-Miner
XML mining
subtrees
bioinformatics
embedding
embedded
embed
treeminger
Tan, H.
Dillon, Tharam S.
Hadzic, Fedja
Chang, Elizabeth
Feng, L.
IMB3-Miner: Mining induced/embedded subtrees by constraining the level of embedding
title IMB3-Miner: Mining induced/embedded subtrees by constraining the level of embedding
title_full IMB3-Miner: Mining induced/embedded subtrees by constraining the level of embedding
title_fullStr IMB3-Miner: Mining induced/embedded subtrees by constraining the level of embedding
title_full_unstemmed IMB3-Miner: Mining induced/embedded subtrees by constraining the level of embedding
title_short IMB3-Miner: Mining induced/embedded subtrees by constraining the level of embedding
title_sort imb3-miner: mining induced/embedded subtrees by constraining the level of embedding
topic mining
IMB3-Miner
XML mining
subtrees
bioinformatics
embedding
embedded
embed
treeminger
url http://hdl.handle.net/20.500.11937/41293