Conformance Checking and Diagnosis in Process Mining Comparing Obser
Process mining techniques can be used to discover, analyze and improve real processes, by extracting models from observed behavior. The aim of this book is conformance checking, one of the main areas of process mining. In conformance checking, existing pr
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Jorge Munoz-Gama
Conformance Checking and Diagnosis in Process Mining Comparing Observed and Modeled Processes
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Lecture Notes in Business Information Processing Series Editors Wil M.P. van der Aalst Eindhoven Technical University, Eindhoven, The Netherlands John Mylopoulos University of Trento, Trento, Italy Michael Rosemann Queensland University of Technology, Brisbane, QLD, Australia Michael J. Shaw University of Illinois, Urbana-Champaign, IL, USA Clemens Szyperski Microsoft Research, Redmond, WA, USA
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More information about this series at http://www.springer.com/series/7911
Jorge Munoz-Gama
Conformance Checking and Diagnosis in Process Mining Comparing Observed and Modeled Processes
123
Jorge Munoz-Gama Departamento de Ciencia de la Computación Pontificia Universidad Católica de Chile, Escuela de Ingeniería Macul, Santiago Chile
ISSN 1865-1348 ISSN 1865-1356 (electronic) Lecture Notes in Business Information Processing ISBN 978-3-319-49450-0 ISBN 978-3-319-49451-7 (eBook) DOI 10.1007/978-3-319-49451-7 Library of Congress Control Number: 2016957478 © Springer International Publishing AG 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
To Loly, Emilio, Alex, and the rest of my family and friends.
Preface
This book encompasses a revised version of the PhD dissertation of Jorge Munoz-Gama written at the Computer Science Department of the Universitat Politècnica de Catalunya (Spain). In 2015, the dissertation won the “Best Process Mining Dissertation Award,” assigned by the IEEE Task Force on Process Mining to the most outstanding PhD thesis, discussed between 2013 and 2014, focused on the area of business process intelligence. In the past few decades, the capability of information systems to generate and record overwhelming amounts o
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