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Two Decades of Pattern Mining: Principles and Methods

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Business Intelligence (eBISS 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 280))

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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”. It aimed at enumerating the complete collection of regularities observed in a given dataset like for instance sets of products purchased together in a supermarket. For two decades, pattern mining has been one of the most active fields in Knowledge Discovery in Databases. This paper presents an overview of pattern mining. We first present the principles of language and interestingness that are two key dimensions for defining a pattern mining process to suit a specific task and a specific dataset. The language defines which patterns can be enumerated (itemsets, sequences, graphs). The interestingness measure defines the archetype of patterns to mine (regularities, contrasts or anomalies). Starting from a language and an interestingness measure, we depict the two main categories of pattern mining methods: enumerating all the patterns whose interestingness exceeds a user-specified threshold (satisfaction problem) or enumerating all the patterns whose interest is maximum (optimization problem). Finally, we present an overview of interactive pattern mining which aims at discovering the user’s interest while mining relevant patterns.

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Notes

  1. 1.

    www.core.edu.au, 2010.

  2. 2.

    www.kdd.org.

  3. 3.

    PKDD was attached in 2001 to ECML (European Conference on Machine Learning) then the two conferences merged in 2008. Since 2008, PKDD corresponds to ECML/PKDD.

  4. 4.

    www.ecmlpkdd.org.

  5. 5.

    www.pakdd.org.

  6. 6.

    www.cs.uvm.edu/~icdm.

  7. 7.

    www.siam.org/meetings/archives.php#sdm.

  8. 8.

    Conversely, pattern mining is not well adapted to continuous data even if there exist proposals [15, 16].

  9. 9.

    In this paper, we use the same language for mined patterns and the dataset. It is nevertheless possible to use distinct languages benefiting from a cover relation.

  10. 10.

    This toy example is inspired from an article found on the Web site mic.com.

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Acknowledgments

The author would like to thank Bruno Crémilleux, Arnaud Giacometti and Marc Plantevit for many fruitful discussions. The author would also like to thank the anonymous reviewers and Patrick Marcel for their helpful comments that greatly contributed to improve the final version of the paper.

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Authors and Affiliations

  1. University of Tours, Blois, France

    Arnaud Soulet

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  1. Arnaud Soulet
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Correspondence to Arnaud Soulet .

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Editors and Affiliations

  1. University of Tours, Tours, France

    Patrick Marcel

  2. Dept. of Computer and Decision Engg. (CoDE), Universite Libre de Bruxelles, Brussels, Belgium

    Esteban Zimányi

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Soulet, A. (2017). Two Decades of Pattern Mining: Principles and Methods. In: Marcel, P., Zimányi, E. (eds) Business Intelligence. eBISS 2016. Lecture Notes in Business Information Processing, vol 280. Springer, Cham. https://doi.org/10.1007/978-3-319-61164-8_3

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