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Mining Goal Refinement Patterns: Distilling Know-How from Data

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Conceptual Modeling (ER 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10650))

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Abstract

Goal models play an important role by providing a hierarchic representation of stakeholder intent, and by providing a representation of lower-level subgoals that must be achieved to enable the achievement of higher-level goals. A goal model can be viewed as a composition of a number of goal refinement patterns that relate parent goals to subgoals. In this paper, we offer a means for mining these patterns from enterprise event logs and a technique to leverage vector representations of words and phrases to compose these patterns to obtain complete goal models. The resulting machinery can be quiote powerful in its ability to mine know-how or constitutive norms. We offer an empirical evaluation using both real-life and synthetic datasets.

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Notes

  1. 1.

    http://www.processmining.org/_media/tutorial/repairexample.zip.

  2. 2.

    https://www.win.tue.nl/bpi/doku.php?id=2015:challenge.

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Authors and Affiliations

  1. Department of Informatics, State Polytechnic of Batam, Batam, 29461, Indonesia

    Metta Santiputri

  2. Department of Computer Science and Engineering, University of Calcutta, Kolkata, India

    Novarun Deb & Nabendu Chaki

  3. Decision Systems Lab, School of Computing and IT, University of Wollongong, Wollongong, NSW, 2522, Australia

    Muhammad Asjad Khan, Aditya Ghose & Hoa Dam

Authors
  1. Metta Santiputri
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  2. Novarun Deb
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  3. Muhammad Asjad Khan
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  4. Aditya Ghose
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  5. Hoa Dam
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  6. Nabendu Chaki
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Corresponding author

Correspondence to Aditya Ghose .

Editor information

Editors and Affiliations

  1. University of Klagenfurt, Klagenfurt, Austria

    Heinrich C. Mayr

  2. Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

    Giancarlo Guizzardi

  3. Victoria University of Wellington, Wellington, New Zealand

    Hui Ma

  4. Valencia University of Technology, Valencia, Spain

    Oscar Pastor

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Santiputri, M., Deb, N., Khan, M.A., Ghose, A., Dam, H., Chaki, N. (2017). Mining Goal Refinement Patterns: Distilling Know-How from Data. In: Mayr, H., Guizzardi, G., Ma, H., Pastor, O. (eds) Conceptual Modeling. ER 2017. Lecture Notes in Computer Science(), vol 10650. Springer, Cham. https://doi.org/10.1007/978-3-319-69904-2_6

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  • DOI: https://doi.org/10.1007/978-3-319-69904-2_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69903-5

  • Online ISBN: 978-3-319-69904-2

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