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20 years of pattern mining: a bibliometric survey

Authors:

Arnaud Giacometti,

Dominique H. Li,

Patrick Marcel,

Arnaud SouletAuthors Info & Claims

ACM SIGKDD Explorations Newsletter, Volume 15, Issue 1

Pages 41 - 50

https://doi.org/10.1145/2594473.2594480

Published: 17 March 2014 Publication History

Abstract

In 1993, Rakesh Agrawal, Tomasz Imielinski and Arun N. Swami published one of the founding papers of Pattern Mining: "Mining Association Rules between Sets of Items in Large Databases". Beyond the introduction to a new problem, it introduced a new methodology in terms of resolution and evaluation. For two decades, Pattern Mining has been one of the most active fields in Knowledge Discovery in Databases. This paper provides a bibliometric survey of the literature relying on 1,087 publications from five major international conferences: KDD, PKDD, PAKDD, ICDM and SDM. We first measured a slowdown of research dedicated to Pattern Mining while the KDD field continues to grow. Then, we quantified the main contributions with respect to languages, constraints and condensed representations to outline the current directions. We observe a sophistication of languages over the last 20 years, although association rules and itemsets are so far the most studied ones. As expected, the minimal support constraint predominates the extraction of patterns with approximately 50% of the publications. Finally, condensed representations used in 10% of the papers had relative success particularly between 2005 and 2008.

References

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J. L. Balcázar. Minimum-size bases of association rules. In W. Daelemans, B. Goethals, and K. Morik, editors, ECML/PKDD (1), volume 5211 of Lecture Notes in Computer Science, pages 86--101. Springer, 2008.

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J. Han, H. Cheng, D. Xin, and X. Yan. Frequent pattern mining: current status and future directions. Data Min. Knowl. Discov., 15(1):55--86, 2007.

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Cited By

Mathonat RNurbakova DBoulicaut JKaytoue M(2021)Anytime mining of sequential discriminative patterns in labeled sequencesKnowledge and Information Systems10.1007/s10115-020-01523-763:2(439-476)Online publication date: 1-Feb-2021
https://dl.acm.org/doi/10.1007/s10115-020-01523-7
Mathonat RNurbakova DBoulicaut JKaytoue M(2019)SeqScout: Using a Bandit Model to Discover Interesting Subgroups in Labeled Sequences2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA.2019.00022(81-90)Online publication date: Oct-2019
https://doi.org/10.1109/DSAA.2019.00022
Fang DWang LYang PChen L(2019)Mining high influence co-location patterns from instances with attributesEvolutionary Intelligence10.1007/s12065-019-00321-7Online publication date: 18-Nov-2019
https://doi.org/10.1007/s12065-019-00321-7
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Index Terms

20 years of pattern mining: a bibliometric survey
1. General and reference
  1. Document types
    1. Surveys and overviews
2. Information systems
  1. Information systems applications
    1. Data mining

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Information & Contributors

Information

Published In

cover image ACM SIGKDD Explorations Newsletter

ACM SIGKDD Explorations Newsletter Volume 15, Issue 1

June 2013

50 pages

ISSN:1931-0145

EISSN:1931-0153

DOI:10.1145/2594473

Editors:
Bart Goethals
University of Antwerp, Belgium
,
Charu Aggarwal
IBM T. J. Watson Research Center in Yorktown Heights, New York
,
Srinivasan Parthasarathy
The Ohio State University, Columbus, OH
,
Ankur Teredesai
University of Washington, Seattle, Washington

Issue’s Table of Contents

Copyright © 2014 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 March 2014

Published in SIGKDD Volume 15, Issue 1

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Cited By

Mathonat RNurbakova DBoulicaut JKaytoue M(2021)Anytime mining of sequential discriminative patterns in labeled sequencesKnowledge and Information Systems10.1007/s10115-020-01523-763:2(439-476)Online publication date: 1-Feb-2021
https://dl.acm.org/doi/10.1007/s10115-020-01523-7
Mathonat RNurbakova DBoulicaut JKaytoue M(2019)SeqScout: Using a Bandit Model to Discover Interesting Subgroups in Labeled Sequences2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA.2019.00022(81-90)Online publication date: Oct-2019
https://doi.org/10.1109/DSAA.2019.00022
Fang DWang LYang PChen L(2019)Mining high influence co-location patterns from instances with attributesEvolutionary Intelligence10.1007/s12065-019-00321-7Online publication date: 18-Nov-2019
https://doi.org/10.1007/s12065-019-00321-7
CONDIE TDAS AINTERLANDI MSHKAPSKY AYANG MZANIOLO C(2018)Scaling-up reasoning and advanced analytics on BigDataTheory and Practice of Logic Programming10.1017/S147106841800041818:5-6(806-845)Online publication date: 5-Sep-2018
https://doi.org/10.1017/S1471068418000418
MihelăźIć MDźEroski SLavraăź NźMuc T(2018)Redescription mining augmented with random forest of multi-target predictive clustering treesJournal of Intelligent Information Systems10.1007/s10844-017-0448-550:1(63-96)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1007/s10844-017-0448-5
Belfodil AKuznetsov SRobardet CKaytoue M(2017)Mining convex polygon patterns with formal concept analysisProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3172077.3172085(1425-1432)Online publication date: 19-Aug-2017
https://dl.acm.org/doi/10.5555/3172077.3172085
Amagata DHara T(2017)Mining Top-k Co-Occurrence Patterns across Multiple StreamsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.272853729:10(2249-2262)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.1109/TKDE.2017.2728537
Bosc GTan PBoulicaut JRaissi CKaytoue M(2017)A Pattern Mining Approach to Study Strategy Balance in RTS GamesIEEE Transactions on Computational Intelligence and AI in Games10.1109/TCIAIG.2015.25118199:2(123-132)Online publication date: Jun-2017
https://doi.org/10.1109/TCIAIG.2015.2511819
Ramirez-Atencia CRodríguez-Fernández VGonzalez-Pardo ACamacho D(2017)New Artificial Intelligence approaches for future UAV Ground Control Stations2017 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2017.7969645(2775-2782)Online publication date: 5-Jun-2017
https://dl.acm.org/doi/10.1109/CEC.2017.7969645
Soulet A(2017)Two Decades of Pattern Mining: Principles and MethodsBusiness Intelligence10.1007/978-3-319-61164-8_3(59-78)Online publication date: 4-Jul-2017
https://doi.org/10.1007/978-3-319-61164-8_3
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