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Groupware Mail Messages Analysis for Mining Collaborative Processes

Author

Listed:
  • Claudio Di Ciccio

    (Dipartimento di Informatica e Sistemistica "Antonio Ruberti" Sapienza, Universita' di Roma)

  • Massimo Mecella

    (Dipartimento di Informatica e Sistemistica "Antonio Ruberti" Sapienza, Universita' di Roma)

  • Monica Scannapieco

    (Istituto Nazionale di Statistica Via Balbo 16, Roma, Italy)

  • Diego Zardetto

    (Istituto Nazionale di Statistica Via Balbo 16, Roma, Italy)

  • Tiziana Catarci

    (Dipartimento di Informatica e Sistemistica "Antonio Ruberti" Sapienza, Universita' di Roma)

Abstract

Artful business processes are informal processes typically carried out by those people whose work is mental rather than physical (managers, professors, researchers, etc.), the so called "knowledge workers". In this paper we outline how to automatically build, on top of a collection of e-mail messages, a set of workflow models that represent the artful processes which lay behind the knowledge workers activities.

Suggested Citation

  • Claudio Di Ciccio & Massimo Mecella & Monica Scannapieco & Diego Zardetto & Tiziana Catarci, 2011. "Groupware Mail Messages Analysis for Mining Collaborative Processes," DIS Technical Reports 2011-01, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    • Handle: RePEc:aeg:wpaper:2011-1
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    File URL: http://www.dis.uniroma1.it/~bibdis/RePEc/aeg/wpaper/2011-01.pdf
    File Function: First version, 2011
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    Citations

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    Cited by:

    1. Tony Allard & Paul Alvino & Leslie Shing & Allan Wollaber & Joseph Yuen, 2019. "A dataset to facilitate automated workflow analysis," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-22, February.
    2. Claudio Di Ciccio & Massimo Mecella, 2012. "MINERful, a Mining Algorithm for Declarative Process Constraints in MailOfMine," DIS Technical Reports 2012-03, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".

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