Article

2PXMiner: an efficient two pass mining of frequent XML query patterns

Authors:

Liang Huai Yang,

Mong Li Lee,

Wynne Hsu,

Xinyu GuoAuthors Info & Claims

KDD '04: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 731 - 736

https://doi.org/10.1145/1014052.1014148

Published: 22 August 2004 Publication History

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Abstract

Caching the results of frequent query patterns can improve the performance of query evaluation. This paper describes a 2-pass mining algorithm called 2PXMiner to discover frequent XML query patterns. We design 3 data structures to expedite the mining process. Experiments results indicate that 2PXMiner is both efficient and scalable.

References

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Cited By

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Chang T(2016)A Parallel Encoding Method of XML User Query Patterns2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)10.1109/IIAI-AAI.2016.234(1190-1191)Online publication date: Jul-2016
https://doi.org/10.1109/IIAI-AAI.2016.234
Ding QSundarraj G(2013)Frequent Pattern Discovery and Association Rule Mining of XML DataData Mining10.4018/978-1-4666-2455-9.ch044(859-879)Online publication date: 2013
https://doi.org/10.4018/978-1-4666-2455-9.ch044
Ding QSundarraj G(2012)Frequent Pattern Discovery and Association Rule Mining of XML DataXML Data Mining10.4018/978-1-61350-356-0.ch011(243-263)Online publication date: 2012
https://doi.org/10.4018/978-1-61350-356-0.ch011
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Index Terms

2PXMiner: an efficient two pass mining of frequent XML query patterns
1. Information systems
  1. Information systems applications
    1. Data mining

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Information & Contributors

Information

Published In

KDD '04: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining

August 2004

874 pages

ISBN:1581138881

DOI:10.1145/1014052

General Chairs:
Won Kim
Cyber Database Solutions
,
Ronny Kohavi
Amazon.com
,
Program Chairs:
Johannes Gehrke
Cornell University
,
William DuMouchel
AT&T Labs Research

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 August 2004

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KDD04

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KDD04: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 22 - 25, 2004

WA, Seattle, USA

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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

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Chang T(2016)A Parallel Encoding Method of XML User Query Patterns2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)10.1109/IIAI-AAI.2016.234(1190-1191)Online publication date: Jul-2016
https://doi.org/10.1109/IIAI-AAI.2016.234
Ding QSundarraj G(2013)Frequent Pattern Discovery and Association Rule Mining of XML DataData Mining10.4018/978-1-4666-2455-9.ch044(859-879)Online publication date: 2013
https://doi.org/10.4018/978-1-4666-2455-9.ch044
Ding QSundarraj G(2012)Frequent Pattern Discovery and Association Rule Mining of XML DataXML Data Mining10.4018/978-1-61350-356-0.ch011(243-263)Online publication date: 2012
https://doi.org/10.4018/978-1-61350-356-0.ch011
Severyn AMoschitti A(2012)Fast support vector machines for convolution tree kernelsData Mining and Knowledge Discovery10.1007/s10618-012-0276-825:2(325-357)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1007/s10618-012-0276-8
Chang TChen S(2010)A Novel Top-Down Algorithm of Frequent XML Query Pattern MiningProceedings of the 2010 Second International Conference on Computer Engineering and Applications - Volume 0210.1109/ICCEA.2010.205(276-280)Online publication date: 19-Mar-2010
https://dl.acm.org/doi/10.1109/ICCEA.2010.205
Li GFeng JWang JZhou L(2009)Incremental sequence-based frequent query pattern mining from XML queriesData Mining and Knowledge Discovery10.1007/s10618-009-0126-518:3(472-516)Online publication date: 1-Jun-2009
https://dl.acm.org/doi/10.1007/s10618-009-0126-5
Bhowmick S(2009)On the Discovery of Conserved XML Query Patterns for Evolution-Conscious CachingProceedings of the 14th International Conference on Database Systems for Advanced Applications10.1007/978-3-642-00887-0_46(527-542)Online publication date: 16-Mar-2009
https://dl.acm.org/doi/10.1007/978-3-642-00887-0_46
Vilz JBrogneaux ARamdoyal REnglebert VHainaut J(2006)Data conceptualisation for web-based data-centred application designProceedings of the 18th international conference on Advanced Information Systems Engineering10.1007/11767138_15(205-219)Online publication date: 5-Jun-2006
https://dl.acm.org/doi/10.1007/11767138_15
Zhao QBhowmick SGruenwald LHerzog OSchek HFuhr NChowdhury ATeiken W(2005)Mining conserved XML query paths for dynamic-conscious cachingProceedings of the 14th ACM international conference on Information and knowledge management10.1145/1099554.1099596(219-220)Online publication date: 31-Oct-2005
https://dl.acm.org/doi/10.1145/1099554.1099596

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