references.bib

% EXAMPLE 
@book{yaakov_bar-shalom_estimation_2001,
	address = {New York Chichester Weinheim Brisbane Singapore Toronto},
	title = {Estimation with Applications to Tracking and Navigation},
	isbn = {978-0-471-41655-5},
	publisher = {Wiley-Interscience},
	author = {{Yaakov Bar-Shalom} and {X. Rong Li} and {Thiagalingam Kirubarajan}},
	year = {2001}
}

% Tetbook on the topic 
@book{process_mining,
	address = {},
	title = {Process Mining},
	isbn = {978-0-471-41655-5},
	publisher = {Springer, Berlin, Heidelberg},
	author = {{Wil van den Aalst}},
	year = {2016}
}

% References on growing data availablity
@article{hilbert2011worldcapacity,
  title={The world's technological capacity to store, communicate, and compute information},
  author={Hilbert, Martin and L{\'o}pez, Priscila},
  journal={science},
  pages={1200970},
  year={2011},
  publisher={American Association for the Advancement of Science}
}
@article{manyika2011bigdata,
  title={Big data: The next frontier for innovation, competition, and productivity},
  author={Manyika, James and Chui, Michael and Brown, Brad and Bughin, Jacques and Dobbs, Richard and Roxburgh, Charles and Byers, Angela H},
  year={2011}
}
@inproceedings{engineerOfTheFuture,
author="van der Aalst, Wil M. P.",
editor="Mertins, Kai
and B{\'e}naben, Fr{\'e}d{\'e}rick
and Poler, Ra{\'u}l
and Bourri{\`e}res, Jean-Paul",
title="Data Scientist: The Engineer of the Future",
booktitle="Enterprise Interoperability VI",
year="2014",
publisher="Springer International Publishing",
address="Cham",
pages="13--26",
abstract="Although our capabilities to store and process data have been increasing exponentially since the 1960s, suddenly many organizations realize that survival is not possible without exploiting available data intelligently. Out of the blue, ``Big Data'' has become a topic in board-level discussions. The abundance of data will change many jobs across all industries. Moreover, also scientific research is becoming more data-driven. Therefore, we reflect on the emerging data science discipline. Just like computer science emerged as a new discipline from mathematics when computers became abundantly available, we now see the birth of data science as a new discipline driven by the torrents of data available today. We believe that the data scientist will be the engineer of the future. Therefore, Eindhoven University of Technology (TU/e) established the Data Science Center Eindhoven (DSC/e). This article discusses the data science discipline and motivates its importance.",
isbn="978-3-319-04948-9"
}

% Map Reduce for Scalable Process Discovery alternative approaches
@article{evermann2016scalable,
  title={Scalable process discovery using map-reduce},
  author={Evermann, Joerg},
  journal={IEEE Transactions on Services Computing},
  volume={9},
  number={3},
  pages={469--481},
  year={2016},
  publisher={IEEE}
}

% Initial Inductive Mining Paper 
@inproceedings{inductivemining-constructive,
  title={Discovering block-structured process models from event logs-a constructive approach},
  author={Leemans, Sander JJ and Fahland, Dirk and van der Aalst, Wil MP},
  booktitle={International conference on applications and theory of Petri nets and concurrency},
  pages={311--329},
  year={2013},
  organization={Springer}
}
% Extension of IM to infrequent traces
@inproceedings{inductiveinfrequent,
  title={Discovering block-structured process models from event logs containing infrequent behaviour},
  author={Leemans, Sander JJ and Fahland, Dirk and van der Aalst, Wil MP},
  booktitle={International conference on business process management},
  pages={66--78},
  year={2013},
  organization={Springer}
}

% Adaption of IM for scalability while keeping its promises. 
@inproceedings{leemans2015scalable,
  title={Scalable process discovery with guarantees},
  author={Leemans, Sander JJ and Fahland, Dirk and van der Aalst, Wil MP},
  booktitle={International Conference on Enterprise, Business-Process and Information Systems Modeling},
  pages={85--101},
  year={2015},
  organization={Springer}
}

% Map-Reduce 
@article{evermann2016scalable,
  title={Scalable process discovery using map-reduce},
  author={Evermann, Joerg},
  journal={IEEE Transactions on Services Computing},
  volume={9},
  number={3},
  pages={469--481},
  year={2016},
  publisher={IEEE}
}

% Linear Time Complexity
@article{evermann2016scalable,
  title={Scalable process discovery using map-reduce},
  author={Evermann, Joerg},
  journal={IEEE Transactions on Services Computing},
  volume={9},
  number={3},
  pages={469--481},
  year={2016},
  publisher={IEEE}
}

% Simplyfing models
@article{fahland2013simplifying,
  title={Simplifying discovered process models in a controlled manner},
  author={Fahland, Dirk and Van Der Aalst, Wil MP},
  journal={Information Systems},
  volume={38},
  number={4},
  pages={585--605},
  year={2013},
  publisher={Elsevier}
}

% The ProM Framework 
@inproceedings{van2005prom,
  title={The ProM framework: A new era in process mining tool support},
  author={Van Dongen, Boudewijn F and de Medeiros, Ana Karla A and Verbeek, HMW and Weijters, AJMM and Van Der Aalst, Wil MP},
  booktitle={International conference on application and theory of petri nets},
  pages={444--454},
  year={2005},
  organization={Springer}
}

% Genetic Mining on Trees to guarantee soundness
@article{van2011geneticsoundness,
  title={Improving the representational bias of process mining using genetic tree mining},
  author={van der Aalst, W and Buijs, JCAM and van Dongen, B},
  journal={SIMPDA 2011 Procedings},
  year={2011}
}

% Among others: Translation of Trees to Petri-Nets: 
@inproceedings{buijs2012treetranslation,
  title={A genetic algorithm for discovering process trees},
  author={Buijs, Joos CAM and van Dongen, Boudewijn F and van der Aalst, Wil MP},
  booktitle={Evolutionary Computation (CEC), 2012 IEEE Congress on},
  pages={1--8},
  year={2012},
  organization={IEEE}
}

% Beginnings of Process Modelling
@article{processessoftware,
  title={Discovering models of software processes from event-based data},
  author={Cook, Jonathan E and Wolf, Alexander L},
  journal={ACM Transactions on Software Engineering and Methodology (TOSEM)},
  volume={7},
  number={3},
  pages={215--249},
  year={1998},
  publisher={ACM}
}

% First Approaches using DAGS
@inproceedings{agrawal1998mining,
  title={Mining process models from workflow logs},
  author={Agrawal, Rakesh and Gunopulos, Dimitrios and Leymann, Frank},
  booktitle={International Conference on Extending Database Technology},
  pages={467--483},
  year={1998},
  organization={Springer}
}

% Machine Learning approach
@article{herbst2000integrating,
  title={Integrating machine learning and workflow management to support acquisition and adaptation of workflow models},
  author={Herbst, Joachim and Karagiannis, Dimitris},
  journal={Intelligent Systems in Accounting, Finance \& Management},
  volume={9},
  number={2},
  pages={67--92},
  year={2000},
  publisher={Wiley Online Library}
}

% Differences
@article{cook1999differences,
  title={Software process validation: quantitatively measuring the correspondence of a process to a model},
  author={Cook, Jonathan E and Wolf, Alexander L},
  journal={ACM Transactions on Software Engineering and Methodology (TOSEM)},
  volume={8},
  number={2},
  pages={147--176},
  year={1999},
  publisher={ACM}
}

% Discussion 
@misc{van2004processagenda,
  title={Process mining: a research agenda},
  author={Van der Aalst, Wil MP and Weijters, AJMM},
  year={2004},
  publisher={Elsevier}
}

% Pitfalls of Process Modelling
@article{pitfalls,
author = {Rosemann, Michael},
year = {2006},
month = {05},
pages = {377-384},
title = {Potential pitfalls of process modeling: Part A},
volume = {12},
journal = {Business Process Management Journal},
doi = {10.1108/14637150610668024}
}

% Data Mining
@Article{DataMiningPrinciples,
author="Hand, David J.",
title="Principles of Data Mining",
journal="Drug Safety",
year="2007",
month="Jul",
day="01",
volume="30",
number="7",
pages="621--622",
abstract="Data mining is the discovery of interesting, unexpected or valuable structures in large datasets. As such, it has two rather different aspects. One of these concerns large-scale, `global' structures, and the aim is to model the shapes, or features of the shapes, of distributions. The other concerns small-scale, `local' structures, and the aim is to detect these anomalies and decide if they are real or chance occurrences. In the context of signal detection in the pharmaceutical sector, most interest lies in the second of the above two aspects; however, signal detection occurs relative to an assumed background model, therefore, some discussion of the first aspect is also necessary. This paper gives a lightning overview of data mining and its relation to statistics, with particular emphasis on tools for the detection of adverse drug reactions.",
issn="1179-1942",
doi="10.2165/00002018-200730070-00010",
url="https://doi.org/10.2165/00002018-200730070-00010"
}

% Trees
@book{treeIntroduction,
  title={Introduction to graph theory},
  author={West, Douglas Brent and others},
  volume={2},
  year={2001},
  publisher={Prentice hall Upper Saddle River}
}

% Comparison of Approaches 
@article{aleem2015comparison,
  title={Business process mining approaches: A relative comparison},
  author={Aleem, Saiqa and Capretz, Luiz Fernando and Ahmed, Faheem},
  journal={arXiv preprint arXiv:1507.05654},
  year={2015}
}

% Soundness
@inproceedings{soundness,
  title={Structural patterns for soundness of business process models},
  author={Van Dongen, Boudewijn F and Mendling, Jan and van der Aalst, Wil MP},
  booktitle={null},
  pages={116--128},
  year={2006},
  organization={IEEE}
}

% Graph algorithms
@article{tarjan1972depth,
  title={Depth-first search and linear graph algorithms},
  author={Tarjan, Robert},
  journal={SIAM journal on computing},
  volume={1},
  number={2},
  pages={146--160},
  year={1972},
  publisher={SIAM}
}



% Further examples and usage 
@article{rios2017process,
  title={Process Mining the Credit Suisse Advisory Process},
  author={Rios, Gina Marie and Jacoway, Ian Robert and Feeley, Shannon Colella},
  year={2017},
  publisher={Worcester Polytechnic Institute}
}

% Business Process Management
@book{jeston2014business,
  title={Business process management},
  author={Jeston, John},
  year={2014},
  publisher={Routledge}
}