Data-Driven Process Discovery and Analysis

Third IFIP WG 2.6, 2.12 International Symposium, SIMPDA 2013, Riva del Garda, Italy, August 30, 2013, Revised Selected Papers

  • Paolo Ceravolo
  • Rafael Accorsi
  • Philippe Cudre-Mauroux
Conference proceedings SIMPDA 2013

DOI: 10.1007/978-3-662-46436-6

Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 203)

Table of contents (6 papers)

  1. Front Matter
    Pages I-IX
  2. The Effect of Noise on Mined Declarative Constraints
    Claudio Di Ciccio, Massimo Mecella, Jan Mendling
    Pages 1-24
  3. Towards Collecting Sustainability Data in Supply Chains with Flexible Data Collection Processes
    Gregor Grambow, Nicolas Mundbrod, Jens Kolb, Manfred Reichert
    Pages 25-47
  4. Handling Environment for Publicly Posted Composite Documents
    Helen Balinsky, David Subirós Pérez
    Pages 48-64
  5. Enabling Non-expert Users to Apply Data Mining for Bridging the Big Data Divide
    Roberto Espinosa, Diego García-Saiz, Marta Zorrilla, Jose Jacobo Zubcoff, Jose-Norberto Mazón
    Pages 65-86
  6. Combining Semantic Lifting and Ad-hoc Contextual Analysis in a Data Loss Scenario
    Antonia Azzini, Ernesto Damiani, Francesco Zavatarelli
    Pages 87-109
  7. Comparative Process Mining in Education: An Approach Based on Process Cubes
    Wil M. P. van der Aalst, Shengnan Guo, Pierre Gorissen
    Pages 110-134
  8. Back Matter
    Pages 135-135

About these proceedings

Introduction

This book constitutes the thoroughly refereed proceedings of the Third International Symposium on Data-Driven Process Discovery and Analysis held in Riva del Garda, Italy, in August 2013.

The six revised full papers were carefully selected from 18 submissions. Following the event, authors were given the opportunity to improve their papers with the insights they gained from the symposium. The selected papers cover theoretical issues related to process representation, discovery and analysis or provide practical and operational experiences in process discovery and analysis.

Keywords

BPM business process management data mining process analysis process mining process optimization

Editors and affiliations

  • Paolo Ceravolo
    • 1
  • Rafael Accorsi
    • 2
  • Philippe Cudre-Mauroux
    • 3
  1. 1.Università degli Studi di MilanoCremaItaly
  2. 2.TelematicsUniversity of FreiburgFreiburgGermany
  3. 3.University of FribourgFribourgSwitzerland

Bibliographic information

  • Copyright Information IFIP International Federation for Information Processing 2015
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-662-46435-9
  • Online ISBN 978-3-662-46436-6
  • Series Print ISSN 1865-1348
  • Series Online ISSN 1865-1356