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Annotating and Mining for Effects of Processes

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Conceptual Modeling (ER 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9974))

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Abstract

We provide a novel explicit annotation of a process model by way of accumulating effects of individual tasks specified by analysts using belief bases and computing the accumulated effect up to the point of execution of the process model in an automated manner. This technique permits the analyst to specify immediate effect annotations in a practitioner-accessible simple propositional logic formulas and generates a sequence of tasks along with cumulative effects, called effect logs. Further we propose and solve an effect mining problem, that is, given an effect log discover the process model with effect annotations of individual tasks which is close to the original annotated process model.

S. Roy—This work was done when the author visited University of Wollongong during July–Dec’14 to work on Infosys-CRC funded project on data-driven process discovery.

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Notes

  1. 1.

    Process models captured using industry standard notation BPMN.

  2. 2.

    we shall drop the subscript \({\mathbf {P}}\) when it is clear from the context.

  3. 3.

    For the sake of rigor \(\mathcal{P}\) can be partitioned into two sets \(\mathcal{P}= {\mathcal{P}}_t \uplus {\mathcal{P}}_x\), where tasks are annotated with symbols from \({\mathcal{P}}_t\), and conditions on choices come from \({\mathcal{P}}_x\).

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Author information

Authors and Affiliations

  1. Infosys Ltd., # 44 Electronics City, Hosur Road, Bangalore, 560 100, India

    Suman Roy

  2. School of Computer Science and Software Engineering, University of Wollongong, Wollongong, NSW, 2500, Australia

    Metta Santiputri & Aditya Ghose

Authors
  1. Suman Roy
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  2. Metta Santiputri
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  3. Aditya Ghose
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Corresponding author

Correspondence to Suman Roy .

Editor information

Editors and Affiliations

  1. CEDRIC-CNAM & ESSEC Business School, Cergy-Pontoise, France

    Isabelle Comyn-Wattiau

  2. Kyoto University , Kyoto, Japan

    Katsumi Tanaka

  3. Drexel University , Philadelphia, Pennsylvania, USA

    Il-Yeol Song

  4. Nagoya University , Nagoya, Japan

    Shuichiro Yamamoto

  5. Tokyo Institute of Technology , Tokyo, Japan

    Motoshi Saeki

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Roy, S., Santiputri, M., Ghose, A. (2016). Annotating and Mining for Effects of Processes. In: Comyn-Wattiau, I., Tanaka, K., Song, IY., Yamamoto, S., Saeki, M. (eds) Conceptual Modeling. ER 2016. Lecture Notes in Computer Science(), vol 9974. Springer, Cham. https://doi.org/10.1007/978-3-319-46397-1_24

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  • DOI: https://doi.org/10.1007/978-3-319-46397-1_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46396-4

  • Online ISBN: 978-3-319-46397-1

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