Event stream-based process discovery using abstract representations

[1]  Wil M. P. van der Aalst,et al.  RapidProM: Mine Your Processes and Not Just Your Data , 2017, ArXiv.

[2]  Wil M. P. van der Aalst,et al.  Scientific workflows for process mining: building blocks, scenarios, and implementation , 2015, International Journal on Software Tools for Technology Transfer.

[3]  Wil M. P. van der Aalst,et al.  Process Mining , 2016, Springer Berlin Heidelberg.

[4]  Thomas Seidl,et al.  Efficient Process Discovery From Event Streams Using Sequential Pattern Mining , 2015, 2015 IEEE Symposium Series on Computational Intelligence.

[5]  Alessandro Sperduti,et al.  Online Discovery of Declarative Process Models from Event Streams , 2015, IEEE Transactions on Services Computing.

[6]  Tao Li,et al.  Event Mining: Algorithms and Applications , 2015 .

[7]  Boudewijn F. van Dongen,et al.  Avoiding Over-Fitting in ILP-Based Process Discovery , 2015, BPM.

[8]  Sander J. J. Leemans,et al.  Scalable Process Discovery with Guarantees , 2015, BMMDS/EMMSAD.

[9]  Josep Carmona,et al.  Process Discovery Algorithms Using Numerical Abstract Domains , 2014, IEEE Transactions on Knowledge and Data Engineering.

[10]  Gordon S. Blair,et al.  Constructs Competition Miner: Process Control-Flow Discovery of BP-Domain Constructs , 2014, BPM.

[11]  Wil M.P. van der Aalst,et al.  Control-flow discovery from event streams , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[12]  Boudewijn F. van Dongen,et al.  Quality Dimensions in Process Discovery: The Importance of Fitness, Precision, Generalization and Simplicity , 2014, Int. J. Cooperative Inf. Syst..

[13]  Mykola Pechenizkiy,et al.  Dealing With Concept Drifts in Process Mining , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[14]  Sander J. J. Leemans,et al.  Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour , 2013, Business Process Management Workshops.

[15]  Alessandro Sperduti,et al.  A Lossy Counting Based Approach for Learning on Streams of Graphs on a Budget , 2013, IJCAI.

[16]  Sander J. J. Leemans,et al.  Discovering Block-Structured Process Models from Event Logs - A Constructive Approach , 2013, Petri Nets.

[17]  Bart Baesens,et al.  A multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logs , 2012, Inf. Syst..

[18]  Rajeev Motwani,et al.  Approximate Frequency Counts over Data Streams , 2012, VLDB.

[19]  A. J. M. M. Weijters,et al.  Flexible Heuristics Miner (FHM) , 2011, 2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).

[20]  Opher Etzion,et al.  Event Processing in Action , 2010 .

[21]  Marios Hadjieleftheriou,et al.  Methods for finding frequent items in data streams , 2010, The VLDB Journal.

[22]  Boudewijn F. van Dongen,et al.  Process Discovery using Integer Linear Programming , 2009, Fundam. Informaticae.

[23]  Jesús S. Aguilar-Ruiz,et al.  Knowledge discovery from data streams , 2009, Intell. Data Anal..

[24]  Lars Michael Kristensen,et al.  Coloured Petri Nets - Modelling and Validation of Concurrent Systems , 2009 .

[25]  Divesh Srivastava,et al.  Forward Decay: A Practical Time Decay Model for Streaming Systems , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[26]  Boudewijn F. van Dongen,et al.  Process Mining: Overview and Outlook of Petri Net Discovery Algorithms , 2009, Trans. Petri Nets Other Model. Concurr..

[27]  Robin Bergenthum,et al.  Process Mining Based on Regions of Languages , 2007, BPM.

[28]  Wil M. P. van der Aalst,et al.  Fuzzy Mining - Adaptive Process Simplification Based on Multi-perspective Metrics , 2007, BPM.

[29]  Lars Michael Kristensen,et al.  Coloured Petri Nets and CPN Tools for modelling and validation of concurrent systems , 2007, International Journal on Software Tools for Technology Transfer.

[30]  Charu C. Aggarwal,et al.  On biased reservoir sampling in the presence of stream evolution , 2006, VLDB.

[31]  S. Muthukrishnan,et al.  Data streams: algorithms and applications , 2005, SODA '03.

[32]  Boudewijn F. van Dongen,et al.  The ProM Framework: A New Era in Process Mining Tool Support , 2005, ICATPN.

[33]  Divyakant Agrawal,et al.  Efficient Computation of Frequent and Top-k Elements in Data Streams , 2005, ICDT.

[34]  Wil M. P. van der Aalst,et al.  Workflow mining: discovering process models from event logs , 2004, IEEE Transactions on Knowledge and Data Engineering.

[35]  Boudewijn F. van Dongen,et al.  Process Mining for Ubiquitous Mobile Systems: An Overview and a Concrete Algorithm , 2004, UMICS.

[36]  Wil M. P. van der Aalst,et al.  Rediscovering workflow models from event-based data using little thumb , 2003, Integr. Comput. Aided Eng..

[37]  Richard M. Karp,et al.  A simple algorithm for finding frequent elements in streams and bags , 2003, TODS.

[38]  Erik D. Demaine,et al.  Frequency Estimation of Internet Packet Streams with Limited Space , 2002, ESA.

[39]  Wil M. P. van der Aalst,et al.  The Application of Petri Nets to Workflow Management , 1998, J. Circuits Syst. Comput..

[40]  Wil M.P. van der Aalst THE APPLICATION OF PETRI NETS TO WORKFLOW MANAGEMENT , 1998, Journal of Circuits, Systems and Computers.

[41]  Tadao Murata,et al.  Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.

[42]  Richard Granger,et al.  Beyond Incremental Processing: Tracking Concept Drift , 1986, AAAI.

[43]  Jeffrey Scott Vitter,et al.  Random sampling with a reservoir , 1985, TOMS.

[44]  Boudewijn F. van Dongen,et al.  Know What You Stream: Generating Event Streams from CPN Models in ProM 6 , 2015, BPM.

[45]  Mark von Rosing,et al.  Business Process Model and Notation - BPMN , 2015, The Complete Business Process Handbook, Vol. I.

[46]  C. Humby,et al.  Process Mining: Data science in Action , 2014 .

[47]  Gordon S. Blair,et al.  Scalable Dynamic Business Process Discovery with the Constructs Competition Miner , 2014, SIMPDA.

[48]  Boudewijn F. van Dongen,et al.  Data Streams in ProM 6: A Single-node Architecture , 2014, BPM.

[49]  Boudewijn F. van Dongen,et al.  Process mining: a two-step approach to balance between underfitting and overfitting , 2008, Software & Systems Modeling.

[50]  Wil M.P. van der Aalst,et al.  Process mining with the HeuristicsMiner algorithm , 2006 .

[51]  R. Motwani,et al.  Chapter 31 – Approximate Frequency Counts over Data Streams , 2002, VLDB 2002.

[52]  JefI’rty C. Schlirrlrrer Beyond incremental processing : Tracking concept drift , 1999 .