research-article

Community evolution detection in time-evolving information networks

Authors:

Alfredo Cuzzocrea,

Francesco FolinoAuthors Info & Claims

EDBT '13: Proceedings of the Joint EDBT/ICDT 2013 Workshops

Pages 93 - 96

https://doi.org/10.1145/2457317.2457333

Published: 18 March 2013 Publication History

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Abstract

In this paper, we propose a framework for representing, modeling and mining time-evolving information networks. Our framework introduces a graph-based model-theoretic approach to represent such networks and how they change over time. Also, we provide a method for supporting matching-based community evolution detection in time-evolving information networks, by identifying several classes of community transitions, along with algorithms that implement them.

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Cited By

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Anwar MLiu CLi J(2019)Discovering and tracking query oriented active online social groups in dynamic information networkWorld Wide Web10.1007/s11280-018-0627-522:4(1819-1854)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s11280-018-0627-5
Anwar MLiu CLi JAnwar T(2017)Discovering and Tracking Active Online Social GroupsWeb Information Systems Engineering – WISE 201710.1007/978-3-319-68783-4_5(59-74)Online publication date: 4-Oct-2017
https://doi.org/10.1007/978-3-319-68783-4_5
Cuzzocrea AFolino FPizzuti CDesai BLarriba-pey JBernardino J(2013)DynamicNetProceedings of the 17th International Database Engineering & Applications Symposium10.1145/2513591.2513658(148-153)Online publication date: 9-Oct-2013
https://dl.acm.org/doi/10.1145/2513591.2513658
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Index Terms

Community evolution detection in time-evolving information networks
1. Information systems
  1. Information storage systems
    1. Storage architectures
      1. Storage network architectures

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Information & Contributors

Information

Published In

EDBT '13: Proceedings of the Joint EDBT/ICDT 2013 Workshops

March 2013

423 pages

ISBN:9781450315999

DOI:10.1145/2457317

General Chair:
Giovanna Guerrini
Università di Genova, Italy

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: 18 March 2013

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EDBT/ICDT '13

EDBT/ICDT '13: Joint 2013 EDBT/ICDT Conferences

March 18 - 22, 2013

Genoa, Italy

Acceptance Rates

EDBT '13 Paper Acceptance Rate 7 of 10 submissions, 70%;

Overall Acceptance Rate 7 of 10 submissions, 70%

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Cited By

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Anwar MLiu CLi J(2019)Discovering and tracking query oriented active online social groups in dynamic information networkWorld Wide Web10.1007/s11280-018-0627-522:4(1819-1854)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s11280-018-0627-5
Anwar MLiu CLi JAnwar T(2017)Discovering and Tracking Active Online Social GroupsWeb Information Systems Engineering – WISE 201710.1007/978-3-319-68783-4_5(59-74)Online publication date: 4-Oct-2017
https://doi.org/10.1007/978-3-319-68783-4_5
Cuzzocrea AFolino FPizzuti CDesai BLarriba-pey JBernardino J(2013)DynamicNetProceedings of the 17th International Database Engineering & Applications Symposium10.1145/2513591.2513658(148-153)Online publication date: 9-Oct-2013
https://dl.acm.org/doi/10.1145/2513591.2513658
Wei EKoh YDobbie G(2013)Finding Maximal Overlapping CommunitiesProceedings of the 15th International Conference on Data Warehousing and Knowledge Discovery - Volume 805710.1007/978-3-642-40131-2_27(309-316)Online publication date: 26-Aug-2013
https://dl.acm.org/doi/10.1007/978-3-642-40131-2_27

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