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Grand Reports: A Tool for Generalizing Association Rule Mining to Numeric Target Values

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Big Data Analytics and Knowledge Discovery (DaWaK 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12393))

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Abstract

Since its introduction in the 1990s, association rule mining(ARM) has been proven as one of the essential concepts in data mining; both in practice as well as in research. Discretization is the only means to deal with numeric target column in today’s association rule mining tools. However, domain experts and decision-makers are used to argue in terms of mean values when it comes to numeric target values. In this paper, we provide a tool that reports mean values of a chosen numeric target column concerning all possible combinations of influencing factors – so-called grand reports. We give an in-depth explanation of the functionalities of the proposed tool. Furthermore, we compare the capabilities of the tool with one of the leading association rule mining tools, i.e., RapidMiner. Moreover, the study delves into the motivation of grand reports and offers some useful insight into their theoretical foundation.

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Notes

  1. 1.

    http://grandreport.me/.

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Acknowledgements

This work has been conducted in the project “ICT programme” which was supported by the European Union through the European Social Fund.

Author information

Authors and Affiliations

  1. Information Systems Group, Tallinn University of Technology, Akadeemia tee 15a, 12618, Tallinn, Estonia

    Sijo Arakkal Peious, Rahul Sharma & Minakshi Kaushik

  2. Faculty of Information and Communication Technology BUITEMS, Quetta, Pakistan

    Syed Attique Shah

  3. Software Science Department, Tallinn University of Technology, Akadeemia tee 15a, 12618, Tallinn, Estonia

    Sadok Ben Yahia

Authors
  1. Sijo Arakkal Peious
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  2. Rahul Sharma
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  3. Minakshi Kaushik
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  4. Syed Attique Shah
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  5. Sadok Ben Yahia
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Corresponding author

Correspondence to Sijo Arakkal Peious .

Editor information

Editors and Affiliations

  1. Department of Library and Information, Yonsei University, Seoul, Korea (Republic of)

    Min Song

  2. Drexel University, Philadelphia, PA, USA

    Il-Yeol Song

  3. Johannes Kepler University of Linz, Linz, Austria

    Gabriele Kotsis

  4. Software Competence Center Hagenberg (Au), Vienna, Wien, Austria

    A Min Tjoa

  5. Johannes Kepler University of Linz, Linz, Oberösterreich, Austria

    Ismail Khalil

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Arakkal Peious, S., Sharma, R., Kaushik, M., Shah, S.A., Yahia, S.B. (2020). Grand Reports: A Tool for Generalizing Association Rule Mining to Numeric Target Values. In: Song, M., Song, IY., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Big Data Analytics and Knowledge Discovery. DaWaK 2020. Lecture Notes in Computer Science(), vol 12393. Springer, Cham. https://doi.org/10.1007/978-3-030-59065-9_3

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  • DOI: https://doi.org/10.1007/978-3-030-59065-9_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59064-2

  • Online ISBN: 978-3-030-59065-9

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