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Archaeology International
Architecture_MPS
Europe and the World: A law review
Film Education Journal
History Education Research Journal
International Journal of Development Education and Global Learning
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Journal of Bentham Studies
London Review of Education
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Research for All
The Journal of the Sylvia Townsend Warner Society
The London Journal of Canadian Studies
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About UCL Press
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Business Process Management : 19th International Conference, BPM 2021, Rome, Italy, September 06–10, 2021, Proceedings
Weighing the Pros and Cons: Process Discovery with Negative Examples
other
Author(s):
Tijs Slaats
,
Søren Debois
,
Christoffer Olling Back
Publication date
(Online):
August 28 2021
Publisher:
Springer International Publishing
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Future Drug Discovery
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Verification of workflow nets
W. Aalst
(1997)
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Discovering Block-Structured Process Models from Event Logs - A Constructive Approach
Sander J. J. Leemans
,
Dirk Fahland
,
Wil M. P. van der Aalst
(2013)
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DecSerFlow: Towards a Truly Declarative Service Flow Language
W. VAN DER AALST
,
M Pesic
(2006)
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Book Chapter
Publication date (Print):
2021
Publication date (Online):
August 28 2021
Pages
: 47-64
DOI:
10.1007/978-3-030-85469-0_6
SO-VID:
10b58afb-f5b3-471d-9af1-514663092de7
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Book chapters
pp. 3
Process Automation and Process Mining in Manufacturing
pp. 17
Cognitive Effectiveness of Representations for Process Mining
pp. 23
RuM: Declarative Process Mining, Distilled
pp. 30
Applications of Automated Planning for Business Process Management
pp. 37
Artifact-Driven Process Monitoring: A Viable Solution to Continuously and Autonomously Monitor Business Processes
pp. 47
Weighing the Pros and Cons: Process Discovery with Negative Examples
pp. 65
A Method for Debugging Process Discovery Pipelines to Analyze the Consistency of Model Properties
pp. 85
Extracting Decision Models from Textual Descriptions of Processes
pp. 105
Robust and Generalizable Predictive Models for Business Processes
pp. 123
Incremental Predictive Process Monitoring: The Next Activity Case
pp. 141
Learning Uncertainty with Artificial Neural Networks for Improved Remaining Time Prediction of Business Processes
pp. 161
Zoom and Enhance: Action Refinement via Subprocesses in Timed Declarative Processes
pp. 179
Delta-BPMN: A Concrete Language and Verifier for Data-Aware BPMN
pp. 197
A Real-Time Method for Detecting Temporary Process Variants in Event Log Data
pp. 217
CoCoMoT: Conformance Checking of Multi-perspective Processes via SMT
pp. 235
Aligning Data-Aware Declarative Process Models and Event Logs
pp. 252
A Discounted Cost Function for Fast Alignments of Business Processes
pp. 273
Task Clustering Method Using User Interaction Logs to Plan RPA Introduction
pp. 289
From Symbolic RPA to Intelligent RPA: Challenges for Developing and Operating Intelligent Software Robots
pp. 327
Multivariate Business Process Representation Learning Utilizing Gramian Angular Fields and Convolutional Neural Networks
pp. 345
Seeing the Forest for the Trees: Group-Oriented Workforce Analytics
pp. 363
A Case Study of Inconsistency in Process Mining Use: Implications for the Theory of Effective Use
pp. 383
A Robust and Accurate Approach to Detect Process Drifts from Event Streams
pp. 417
Graph Autoencoders for Business Process Anomaly Detection
pp. 437
Drivers and Barriers of the Digital Innovation Process – Case Study Insights from a German Public University
pp. 455
A Stakeholder Engagement Model for Process Improvement Initiatives
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