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Article

Time-Evolving relational classification and ensemble methods

Authors:

Jennifer NevilleAuthors Info & Claims

PAKDD'12: Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I

Pages 1 - 13

https://doi.org/10.1007/978-3-642-30217-6_1

Published: 29 May 2012 Publication History

Abstract

Relational networks often evolve over time by the addition, deletion, and changing of links, nodes, and attributes. However, accurately incorporating the full range of temporal dependencies into relational learning algorithms remains a challenge. We propose a novel framework for discovering <em>temporal-relational representations</em> for classification. The framework considers transformations over <em>all</em> the evolving relational components (attributes, edges, and nodes) in order to accurately incorporate temporal dependencies into relational models. Additionally, we propose <em>temporal ensemble methods</em> and demonstrate their effectiveness against traditional and relational ensembles on two real-world datasets. In all cases, the proposed temporal-relational models outperform competing models that ignore temporal information.

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Cited By

Jin DKim SRossi RKoutra DSelcuk Candan KLiu HAkoglu LLuna Dong XTang J(2022)On Generalizing Static Node Embedding to Dynamic SettingsProceedings of the Fifteenth ACM International Conference on Web Search and Data Mining10.1145/3488560.3498428(410-420)Online publication date: 11-Feb-2022
https://dl.acm.org/doi/10.1145/3488560.3498428
Ahmed NDuffield NRossi R(2021)Online Sampling of Temporal NetworksACM Transactions on Knowledge Discovery from Data10.1145/344220215:4(1-27)Online publication date: 18-Apr-2021
https://dl.acm.org/doi/10.1145/3442202
Park HNeville J(2019)Exploiting interaction links for node classification with deep graph neural networksProceedings of the 28th International Joint Conference on Artificial Intelligence10.5555/3367471.3367489(3223-3230)Online publication date: 10-Aug-2019
https://dl.acm.org/doi/10.5555/3367471.3367489
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Time-Evolving relational classification and ensemble methods
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Information & Contributors

Information

Published In

cover image Guide Proceedings

PAKDD'12: Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I

May 2012

616 pages

ISBN:9783642302169

Editors:
Pang-Ning Tan
Department of Computer Science, Michigan State University, 428 S. Shaw Lane, East Lansing, MI
,
Sanjay Chawla
School of Information Technologies, University of Sydney, 1 Cleveland St., Sydney, NSW, Australia
,
Chin Kuan Ho
Faculty of Computing and Informatics, Jalan Multimedia, Multimedia University, 1 Cleveland St., Cyberjaya, Selangor, Malaysia
,
James Bailey
Department of Computing and Information Systems, The University of Melbourne, 111 Barry Street, Melbourne, VIC, Australia

Sponsors

SAS
AOARD: Asian Office of Aerospace Research and Development
PIKOM: PIKOM
AFOSR: AFOSR
MDeC: Multimedia Development Corporation

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 29 May 2012

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Cited By

Jin DKim SRossi RKoutra DSelcuk Candan KLiu HAkoglu LLuna Dong XTang J(2022)On Generalizing Static Node Embedding to Dynamic SettingsProceedings of the Fifteenth ACM International Conference on Web Search and Data Mining10.1145/3488560.3498428(410-420)Online publication date: 11-Feb-2022
https://dl.acm.org/doi/10.1145/3488560.3498428
Ahmed NDuffield NRossi R(2021)Online Sampling of Temporal NetworksACM Transactions on Knowledge Discovery from Data10.1145/344220215:4(1-27)Online publication date: 18-Apr-2021
https://dl.acm.org/doi/10.1145/3442202
Park HNeville J(2019)Exploiting interaction links for node classification with deep graph neural networksProceedings of the 28th International Joint Conference on Artificial Intelligence10.5555/3367471.3367489(3223-3230)Online publication date: 10-Aug-2019
https://dl.acm.org/doi/10.5555/3367471.3367489
Van Vlasselaer VEliassi-Rad TAkoglu LSnoeck MBaesens B(2015)AFRAIDProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 201510.1145/2808797.2810058(659-666)Online publication date: 25-Aug-2015
https://dl.acm.org/doi/10.1145/2808797.2810058
Ahmed NNeville JKompella R(2013)Network SamplingACM Transactions on Knowledge Discovery from Data10.1145/26014388:2(1-56)Online publication date: 1-Jun-2013
https://dl.acm.org/doi/10.1145/2601438
Van Vlasselaer VMeskens JVan Dromme DBaesens BRokne JFaloutsos C(2013)Using social network knowledge for detecting spider constructions in social security fraudProceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1145/2492517.2500292(813-820)Online publication date: 25-Aug-2013
https://dl.acm.org/doi/10.1145/2492517.2500292
Rossi RGallagher BNeville JHenderson KLeonardi SPanconesi AFerragina PGionis A(2013)Modeling dynamic behavior in large evolving graphsProceedings of the sixth ACM international conference on Web search and data mining10.1145/2433396.2433479(667-676)Online publication date: 4-Feb-2013
https://dl.acm.org/doi/10.1145/2433396.2433479
Rossi RGallagher BNeville JHenderson KMille AGandon FMisselis JRabinovich MStaab S(2012)Role-dynamicsProceedings of the 21st International Conference on World Wide Web10.1145/2187980.2188234(997-1006)Online publication date: 16-Apr-2012
https://dl.acm.org/doi/10.1145/2187980.2188234

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