Robust Process Mining with Guarantees: Process Discovery, Conformance Checking and Enhancement
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer International Publishing AG
2022
|
| Schriftenreihe: | Lecture Notes in Business Information Processing Series
v.440 |
| Schlagworte: | |
| Online-Zugang: | DE-2070s |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (478 Seiten) |
| ISBN: | 9783030966553 |
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| 245 | 1 | 0 | |a Robust Process Mining with Guarantees |b Process Discovery, Conformance Checking and Enhancement |
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| 490 | 0 | |a Lecture Notes in Business Information Processing Series |v v.440 | |
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| 505 | 8 | |a Intro -- Preface -- Acknowledgements -- Summary -- Contents -- 1 Introduction -- 1.1 Abstractions in Process Mining -- 1.2 Process Discovery -- 1.3 Conformance Checking -- 1.4 Enhancement & -- Tool Support -- 1.5 Contributions and Structure of this Book -- References -- 2 Preliminaries -- 2.1 Multisets, Traces, Regular Expressions -- 2.2 Process Models -- 2.2.1 Automata -- 2.2.2 Petri Nets -- 2.2.3 Yet Another Workflow Language -- 2.2.4 Business Process Model and Notation -- 2.2.5 Process Trees -- 2.3 Event Logs -- 2.3.1 Atomic Event Logs -- 2.3.2 Non-Atomic Event Logs -- 2.3.3 Richer Logs -- 2.4 Directly Follows Relation -- References -- 3 Process Mining -- 3.1 Different Use Cases, Different Process Mining Techniques -- 3.2 Formal Key Challenges of Process Mining -- 3.2.1 Models with Precise Semantics -- 3.2.2 System - Log - Model Relations -- 3.2.3 Simplicity & -- Balancing Log Criteria -- 3.2.4 An Ideal Technique (1) -- 3.3 Process Discovery -- 3.3.1 Discovery Algorithms Guaranteeing Soundness -- 3.3.2 Other Discovery Algorithms -- 3.3.3 An Ideal Process Discovery Technique (2) -- 3.4 Conformance Checking -- 3.4.1 Log Conformance Checking -- 3.4.2 System Conformance Checking -- 3.4.3 An Ideal Conformance Checking Technique (2) -- 3.5 Enhancement & -- Tool Support -- 3.5.1 Enhancements -- 3.5.2 Process Mining Tools -- 3.5.3 Requirements for Tool Support Beyond Process Discovery and Conformance Checking -- 3.6 Our Approach -- 3.6.1 A Process Discovery Framework -- 3.6.2 A Conformance Checking Framework -- 3.6.3 Enhancement & -- Tool Support -- 3.6.4 Future Work -- References -- 4 Recursive Process Discovery -- 4.1 Recursive Process Discovery -- 4.1.1 An Example of Recursive Process Discovery -- 4.1.2 The IM framework -- 4.1.3 More Technical Examples -- 4.1.4 Guarantees -- 4.2 Rediscoverability | |
| 505 | 8 | |a 4.2.1 Rediscoverability using Abstractions -- 4.2.2 Rediscoverability and the IM framework -- References -- 5 Abstractions -- 5.1 A Canonical Normal Form for Process Trees -- 5.1.1 Reduction Rules -- 5.1.2 Canonicity of the Reduction Rules -- 5.2 Language Uniqueness with Directly Follows Graphs -- 5.2.1 A Class of Trees: Cb -- 5.2.2 Footprints -- 5.2.3 Language Uniqueness -- 5.3 Language Uniqueness with Activity Relations -- 5.3.1 Activity Relations -- 5.3.2 Binary Trees -- 5.3.3 Language Uniqueness -- 5.4 Language Uniqueness with Interleaving -- 5.4.1 Footprint -- 5.4.2 A Class of Trees: Ci -- 5.4.3 Language Uniqueness -- 5.5 Language Uniqueness with Minimum Self-Distance -- 5.5.1 Minimum Self-Distance -- 5.5.2 A Class of Trees: Cm -- 5.5.3 Footprints -- 5.5.4 LC-Property -- 5.5.5 Language Uniqueness -- 5.6 Language Uniqueness with Optionality & -- Inclusive Choice -- 5.6.1 Optionality -- 5.6.2 Optionality in the Directly Follows Graph -- 5.6.3 A Class of Trees: Ccoo -- 5.6.4 Optionality under Sequence -- 5.6.5 Optionality under Inclusive Choice & -- Concurrency -- 5.6.6 Language Uniqueness -- 5.7 Language Uniqueness with non-Atomic Process Models -- 5.7.1 Non-Atomic Process Models -- 5.7.2 Representational Bias of Non-Atomic Models -- 5.7.3 Non-Atomic Directly Follows Graphs & -- Footprints -- 5.7.4 Concurrency Graphs & -- Footprints -- 5.7.5 A Class of Trees: Clc -- 5.7.6 Language Uniqueness -- 5.8 Classes of Process Trees: Revisited -- References -- 6 Discovery Algorithms -- 6.1 Inductive Miner (IM) -- 6.1.1 Example -- 6.1.2 Inductive Miner (IM) -- 6.1.3 Guarantees -- 6.2 Handling Deviating & -- Infrequent Behaviour -- 6.2.1 Deviating & -- Infrequent Behaviour -- 6.2.2 Inductive Miner - infrequent (IMf) -- 6.2.3 Example -- 6.2.4 Guarantees -- 6.3 Handling Incomplete Behaviour -- 6.3.1 Incomplete Behaviour | |
| 505 | 8 | |a 6.3.2 Inductive Miner - incompleteness (IMc) -- 6.3.3 Example -- 6.3.4 Guarantees -- 6.3.5 Finding Cuts: Translation to SMT -- 6.4 Handling More Constructs: , '39'42'"613A''45'47'"603A and '39'42'"613A''45'47'"603A -- 6.4.1 Example -- 6.4.2 Inductive Miner - all operators (IMa) -- 6.4.3 Inductive Miner - infrequent - all operators (IMfa) -- 6.4.4 Guarantees -- 6.5 Handling Non-Atomic Event Logs -- 6.5.1 Non-Atomic Event Logs -- 6.5.2 Inductive Miner - life cycle (IMlc) -- 6.5.3 Inductive Miner - infrequent - life cycle (IMflc) & -- Inductive Miner - incompleteness - life cycle (IMclc) -- 6.5.4 Implementation -- 6.5.5 Guarantees -- 6.6 Handling Large Event Logs -- 6.6.1 Example -- 6.6.2 Inductive Miner - directly follows based framework (IMd framework) -- 6.6.3 Inductive Miner - directly follows (IMd) -- 6.6.4 Inductive Miner - infrequent - directly follows (IMfd) -- 6.6.5 Inductive Miner - incompleteness - directly follows (IMcd) -- 6.6.6 Guarantees -- 6.7 Tool Support -- 6.8 Summary: Choosing a Miner -- References -- 7 Conformance Checking -- 7.1 Projected Conformance Checking Framework -- 7.1.1 Log to Projected Log to DFA -- 7.1.2 Model to Projected Model to DFA -- 7.1.3 Comparing DFAs & -- Measuring -- 7.1.4 Measuring over All Activities -- 7.2 An Example of Non-Conformance and Diagnostic Information -- 7.3 Guarantees -- 7.4 Tool Support -- 7.5 Conclusion -- 7.6 Ideas to Handle Unbounded & -- Weakly Unsound Petri Nets -- References -- 8 Evaluation -- 8.1 Evaluated Process Discovery Algorithms -- 8.2 Scalability of Discovery Algorithms -- 8.2.1 Set-up -- 8.2.2 Results -- 8.2.3 Discussion -- 8.3 Log-Quality Dimensions -- 8.3.1 Event Logs -- 8.3.2 Quantitative -- 8.3.3 Qualitative -- 8.3.4 Conclusion -- 8.4 Rediscoverability & -- its Challenges -- 8.4.1 Incomplete Behaviour -- 8.4.2 Deviating & -- Infrequent Behaviour | |
| 505 | 8 | |a 8.5 Evaluation of Log-Conformance Checking -- 8.5.1 Set-up -- 8.5.2 Results -- 8.5.3 Discussion -- 8.5.4 Evaluation Using the PCC framework -- 8.6 Non-Atomic Behaviour -- 8.6.1 Artificial Log -- 8.6.2 Real-Life Log -- 8.7 Conclusion -- References -- 9 Enhancement & -- Inductive visual Miner -- 9.1 Inductive visual Miner (IvM) -- 9.1.1 Steps & -- Architecture -- 9.1.2 Model Visualisation -- 9.1.3 Controls & -- Parameters -- 9.1.4 Adding Extensions -- 9.2 Deviations -- 9.2.1 Deviations and the PCC framework -- 9.2.2 Deviations and Alignments -- 9.3 Frequency Information -- 9.4 Projecting Performance Information on Process Trees -- 9.5 Animation -- 9.6 Conclusion -- References -- 10 Conclusion -- 10.1 Process Discovery -- 10.2 Conformance Checking -- 10.3 Enhancement & -- Tool Support -- 10.4 Remaining Challenges -- 10.4.1 Detailed -- 10.4.2 Future Work -- References -- Index | |
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| contents | Intro -- Preface -- Acknowledgements -- Summary -- Contents -- 1 Introduction -- 1.1 Abstractions in Process Mining -- 1.2 Process Discovery -- 1.3 Conformance Checking -- 1.4 Enhancement & -- Tool Support -- 1.5 Contributions and Structure of this Book -- References -- 2 Preliminaries -- 2.1 Multisets, Traces, Regular Expressions -- 2.2 Process Models -- 2.2.1 Automata -- 2.2.2 Petri Nets -- 2.2.3 Yet Another Workflow Language -- 2.2.4 Business Process Model and Notation -- 2.2.5 Process Trees -- 2.3 Event Logs -- 2.3.1 Atomic Event Logs -- 2.3.2 Non-Atomic Event Logs -- 2.3.3 Richer Logs -- 2.4 Directly Follows Relation -- References -- 3 Process Mining -- 3.1 Different Use Cases, Different Process Mining Techniques -- 3.2 Formal Key Challenges of Process Mining -- 3.2.1 Models with Precise Semantics -- 3.2.2 System - Log - Model Relations -- 3.2.3 Simplicity & -- Balancing Log Criteria -- 3.2.4 An Ideal Technique (1) -- 3.3 Process Discovery -- 3.3.1 Discovery Algorithms Guaranteeing Soundness -- 3.3.2 Other Discovery Algorithms -- 3.3.3 An Ideal Process Discovery Technique (2) -- 3.4 Conformance Checking -- 3.4.1 Log Conformance Checking -- 3.4.2 System Conformance Checking -- 3.4.3 An Ideal Conformance Checking Technique (2) -- 3.5 Enhancement & -- Tool Support -- 3.5.1 Enhancements -- 3.5.2 Process Mining Tools -- 3.5.3 Requirements for Tool Support Beyond Process Discovery and Conformance Checking -- 3.6 Our Approach -- 3.6.1 A Process Discovery Framework -- 3.6.2 A Conformance Checking Framework -- 3.6.3 Enhancement & -- Tool Support -- 3.6.4 Future Work -- References -- 4 Recursive Process Discovery -- 4.1 Recursive Process Discovery -- 4.1.1 An Example of Recursive Process Discovery -- 4.1.2 The IM framework -- 4.1.3 More Technical Examples -- 4.1.4 Guarantees -- 4.2 Rediscoverability 4.2.1 Rediscoverability using Abstractions -- 4.2.2 Rediscoverability and the IM framework -- References -- 5 Abstractions -- 5.1 A Canonical Normal Form for Process Trees -- 5.1.1 Reduction Rules -- 5.1.2 Canonicity of the Reduction Rules -- 5.2 Language Uniqueness with Directly Follows Graphs -- 5.2.1 A Class of Trees: Cb -- 5.2.2 Footprints -- 5.2.3 Language Uniqueness -- 5.3 Language Uniqueness with Activity Relations -- 5.3.1 Activity Relations -- 5.3.2 Binary Trees -- 5.3.3 Language Uniqueness -- 5.4 Language Uniqueness with Interleaving -- 5.4.1 Footprint -- 5.4.2 A Class of Trees: Ci -- 5.4.3 Language Uniqueness -- 5.5 Language Uniqueness with Minimum Self-Distance -- 5.5.1 Minimum Self-Distance -- 5.5.2 A Class of Trees: Cm -- 5.5.3 Footprints -- 5.5.4 LC-Property -- 5.5.5 Language Uniqueness -- 5.6 Language Uniqueness with Optionality & -- Inclusive Choice -- 5.6.1 Optionality -- 5.6.2 Optionality in the Directly Follows Graph -- 5.6.3 A Class of Trees: Ccoo -- 5.6.4 Optionality under Sequence -- 5.6.5 Optionality under Inclusive Choice & -- Concurrency -- 5.6.6 Language Uniqueness -- 5.7 Language Uniqueness with non-Atomic Process Models -- 5.7.1 Non-Atomic Process Models -- 5.7.2 Representational Bias of Non-Atomic Models -- 5.7.3 Non-Atomic Directly Follows Graphs & -- Footprints -- 5.7.4 Concurrency Graphs & -- Footprints -- 5.7.5 A Class of Trees: Clc -- 5.7.6 Language Uniqueness -- 5.8 Classes of Process Trees: Revisited -- References -- 6 Discovery Algorithms -- 6.1 Inductive Miner (IM) -- 6.1.1 Example -- 6.1.2 Inductive Miner (IM) -- 6.1.3 Guarantees -- 6.2 Handling Deviating & -- Infrequent Behaviour -- 6.2.1 Deviating & -- Infrequent Behaviour -- 6.2.2 Inductive Miner - infrequent (IMf) -- 6.2.3 Example -- 6.2.4 Guarantees -- 6.3 Handling Incomplete Behaviour -- 6.3.1 Incomplete Behaviour 6.3.2 Inductive Miner - incompleteness (IMc) -- 6.3.3 Example -- 6.3.4 Guarantees -- 6.3.5 Finding Cuts: Translation to SMT -- 6.4 Handling More Constructs: , '39'42'"613A''45'47'"603A and '39'42'"613A''45'47'"603A -- 6.4.1 Example -- 6.4.2 Inductive Miner - all operators (IMa) -- 6.4.3 Inductive Miner - infrequent - all operators (IMfa) -- 6.4.4 Guarantees -- 6.5 Handling Non-Atomic Event Logs -- 6.5.1 Non-Atomic Event Logs -- 6.5.2 Inductive Miner - life cycle (IMlc) -- 6.5.3 Inductive Miner - infrequent - life cycle (IMflc) & -- Inductive Miner - incompleteness - life cycle (IMclc) -- 6.5.4 Implementation -- 6.5.5 Guarantees -- 6.6 Handling Large Event Logs -- 6.6.1 Example -- 6.6.2 Inductive Miner - directly follows based framework (IMd framework) -- 6.6.3 Inductive Miner - directly follows (IMd) -- 6.6.4 Inductive Miner - infrequent - directly follows (IMfd) -- 6.6.5 Inductive Miner - incompleteness - directly follows (IMcd) -- 6.6.6 Guarantees -- 6.7 Tool Support -- 6.8 Summary: Choosing a Miner -- References -- 7 Conformance Checking -- 7.1 Projected Conformance Checking Framework -- 7.1.1 Log to Projected Log to DFA -- 7.1.2 Model to Projected Model to DFA -- 7.1.3 Comparing DFAs & -- Measuring -- 7.1.4 Measuring over All Activities -- 7.2 An Example of Non-Conformance and Diagnostic Information -- 7.3 Guarantees -- 7.4 Tool Support -- 7.5 Conclusion -- 7.6 Ideas to Handle Unbounded & -- Weakly Unsound Petri Nets -- References -- 8 Evaluation -- 8.1 Evaluated Process Discovery Algorithms -- 8.2 Scalability of Discovery Algorithms -- 8.2.1 Set-up -- 8.2.2 Results -- 8.2.3 Discussion -- 8.3 Log-Quality Dimensions -- 8.3.1 Event Logs -- 8.3.2 Quantitative -- 8.3.3 Qualitative -- 8.3.4 Conclusion -- 8.4 Rediscoverability & -- its Challenges -- 8.4.1 Incomplete Behaviour -- 8.4.2 Deviating & -- Infrequent Behaviour 8.5 Evaluation of Log-Conformance Checking -- 8.5.1 Set-up -- 8.5.2 Results -- 8.5.3 Discussion -- 8.5.4 Evaluation Using the PCC framework -- 8.6 Non-Atomic Behaviour -- 8.6.1 Artificial Log -- 8.6.2 Real-Life Log -- 8.7 Conclusion -- References -- 9 Enhancement & -- Inductive visual Miner -- 9.1 Inductive visual Miner (IvM) -- 9.1.1 Steps & -- Architecture -- 9.1.2 Model Visualisation -- 9.1.3 Controls & -- Parameters -- 9.1.4 Adding Extensions -- 9.2 Deviations -- 9.2.1 Deviations and the PCC framework -- 9.2.2 Deviations and Alignments -- 9.3 Frequency Information -- 9.4 Projecting Performance Information on Process Trees -- 9.5 Animation -- 9.6 Conclusion -- References -- 10 Conclusion -- 10.1 Process Discovery -- 10.2 Conformance Checking -- 10.3 Enhancement & -- Tool Support -- 10.4 Remaining Challenges -- 10.4.1 Detailed -- 10.4.2 Future Work -- References -- Index |
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| dewey-full | 006.312 |
| dewey-hundreds | 000 - Computer science, information, general works |
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| discipline | Informatik Wirtschaftswissenschaften |
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Log - Model Relations -- 3.2.3 Simplicity &amp -- Balancing Log Criteria -- 3.2.4 An Ideal Technique (1) -- 3.3 Process Discovery -- 3.3.1 Discovery Algorithms Guaranteeing Soundness -- 3.3.2 Other Discovery Algorithms -- 3.3.3 An Ideal Process Discovery Technique (2) -- 3.4 Conformance Checking -- 3.4.1 Log Conformance Checking -- 3.4.2 System Conformance Checking -- 3.4.3 An Ideal Conformance Checking Technique (2) -- 3.5 Enhancement &amp -- Tool Support -- 3.5.1 Enhancements -- 3.5.2 Process Mining Tools -- 3.5.3 Requirements for Tool Support Beyond Process Discovery and Conformance Checking -- 3.6 Our Approach -- 3.6.1 A Process Discovery Framework -- 3.6.2 A Conformance Checking Framework -- 3.6.3 Enhancement &amp -- Tool Support -- 3.6.4 Future Work -- References -- 4 Recursive Process Discovery -- 4.1 Recursive Process Discovery -- 4.1.1 An Example of Recursive Process Discovery -- 4.1.2 The IM framework -- 4.1.3 More Technical Examples -- 4.1.4 Guarantees -- 4.2 Rediscoverability</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">4.2.1 Rediscoverability using Abstractions -- 4.2.2 Rediscoverability and the IM framework -- References -- 5 Abstractions -- 5.1 A Canonical Normal Form for Process Trees -- 5.1.1 Reduction Rules -- 5.1.2 Canonicity of the Reduction Rules -- 5.2 Language Uniqueness with Directly Follows Graphs -- 5.2.1 A Class of Trees: Cb -- 5.2.2 Footprints -- 5.2.3 Language Uniqueness -- 5.3 Language Uniqueness with Activity Relations -- 5.3.1 Activity Relations -- 5.3.2 Binary Trees -- 5.3.3 Language Uniqueness -- 5.4 Language Uniqueness with Interleaving -- 5.4.1 Footprint -- 5.4.2 A Class of Trees: Ci -- 5.4.3 Language Uniqueness -- 5.5 Language Uniqueness with Minimum Self-Distance -- 5.5.1 Minimum Self-Distance -- 5.5.2 A Class of Trees: Cm -- 5.5.3 Footprints -- 5.5.4 LC-Property -- 5.5.5 Language Uniqueness -- 5.6 Language Uniqueness with Optionality &amp -- Inclusive Choice -- 5.6.1 Optionality -- 5.6.2 Optionality in the Directly Follows Graph -- 5.6.3 A Class of Trees: Ccoo -- 5.6.4 Optionality under Sequence -- 5.6.5 Optionality under Inclusive Choice &amp -- Concurrency -- 5.6.6 Language Uniqueness -- 5.7 Language Uniqueness with non-Atomic Process Models -- 5.7.1 Non-Atomic Process Models -- 5.7.2 Representational Bias of Non-Atomic Models -- 5.7.3 Non-Atomic Directly Follows Graphs &amp -- Footprints -- 5.7.4 Concurrency Graphs &amp -- Footprints -- 5.7.5 A Class of Trees: Clc -- 5.7.6 Language Uniqueness -- 5.8 Classes of Process Trees: Revisited -- References -- 6 Discovery Algorithms -- 6.1 Inductive Miner (IM) -- 6.1.1 Example -- 6.1.2 Inductive Miner (IM) -- 6.1.3 Guarantees -- 6.2 Handling Deviating &amp -- Infrequent Behaviour -- 6.2.1 Deviating &amp -- Infrequent Behaviour -- 6.2.2 Inductive Miner - infrequent (IMf) -- 6.2.3 Example -- 6.2.4 Guarantees -- 6.3 Handling Incomplete Behaviour -- 6.3.1 Incomplete Behaviour</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">6.3.2 Inductive Miner - incompleteness (IMc) -- 6.3.3 Example -- 6.3.4 Guarantees -- 6.3.5 Finding Cuts: Translation to SMT -- 6.4 Handling More Constructs: , '39'42'"613A''45'47'"603A and '39'42'"613A''45'47'"603A -- 6.4.1 Example -- 6.4.2 Inductive Miner - all operators (IMa) -- 6.4.3 Inductive Miner - infrequent - all operators (IMfa) -- 6.4.4 Guarantees -- 6.5 Handling Non-Atomic Event Logs -- 6.5.1 Non-Atomic Event Logs -- 6.5.2 Inductive Miner - life cycle (IMlc) -- 6.5.3 Inductive Miner - infrequent - life cycle (IMflc) &amp -- Inductive Miner - incompleteness - life cycle (IMclc) -- 6.5.4 Implementation -- 6.5.5 Guarantees -- 6.6 Handling Large Event Logs -- 6.6.1 Example -- 6.6.2 Inductive Miner - directly follows based framework (IMd framework) -- 6.6.3 Inductive Miner - directly follows (IMd) -- 6.6.4 Inductive Miner - infrequent - directly follows (IMfd) -- 6.6.5 Inductive Miner - incompleteness - directly follows (IMcd) -- 6.6.6 Guarantees -- 6.7 Tool Support -- 6.8 Summary: Choosing a Miner -- References -- 7 Conformance Checking -- 7.1 Projected Conformance Checking Framework -- 7.1.1 Log to Projected Log to DFA -- 7.1.2 Model to Projected Model to DFA -- 7.1.3 Comparing DFAs &amp -- Measuring -- 7.1.4 Measuring over All Activities -- 7.2 An Example of Non-Conformance and Diagnostic Information -- 7.3 Guarantees -- 7.4 Tool Support -- 7.5 Conclusion -- 7.6 Ideas to Handle Unbounded &amp -- Weakly Unsound Petri Nets -- References -- 8 Evaluation -- 8.1 Evaluated Process Discovery Algorithms -- 8.2 Scalability of Discovery Algorithms -- 8.2.1 Set-up -- 8.2.2 Results -- 8.2.3 Discussion -- 8.3 Log-Quality Dimensions -- 8.3.1 Event Logs -- 8.3.2 Quantitative -- 8.3.3 Qualitative -- 8.3.4 Conclusion -- 8.4 Rediscoverability &amp -- its Challenges -- 8.4.1 Incomplete Behaviour -- 8.4.2 Deviating &amp -- Infrequent Behaviour</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">8.5 Evaluation of Log-Conformance Checking -- 8.5.1 Set-up -- 8.5.2 Results -- 8.5.3 Discussion -- 8.5.4 Evaluation Using the PCC framework -- 8.6 Non-Atomic Behaviour -- 8.6.1 Artificial Log -- 8.6.2 Real-Life Log -- 8.7 Conclusion -- References -- 9 Enhancement &amp -- Inductive visual Miner -- 9.1 Inductive visual Miner (IvM) -- 9.1.1 Steps &amp -- Architecture -- 9.1.2 Model Visualisation -- 9.1.3 Controls &amp -- Parameters -- 9.1.4 Adding Extensions -- 9.2 Deviations -- 9.2.1 Deviations and the PCC framework -- 9.2.2 Deviations and Alignments -- 9.3 Frequency Information -- 9.4 Projecting Performance Information on Process Trees -- 9.5 Animation -- 9.6 Conclusion -- References -- 10 Conclusion -- 10.1 Process Discovery -- 10.2 Conformance Checking -- 10.3 Enhancement &amp -- Tool Support -- 10.4 Remaining Challenges -- 10.4.1 Detailed -- 10.4.2 Future Work -- References -- Index</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Process mining</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Prozessanalyse</subfield><subfield code="g">Prozessmanagement</subfield><subfield code="0">(DE-588)4496282-4</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)4113937-9</subfield><subfield code="a">Hochschulschrift</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Prozessanalyse</subfield><subfield code="g">Prozessmanagement</subfield><subfield code="0">(DE-588)4496282-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="a">Leemans, Sander J. J.</subfield><subfield code="t">Robust Process Mining with Guarantees</subfield><subfield code="d">Cham : Springer International Publishing AG,c2022</subfield><subfield code="z">9783030966546</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-PQE</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034185119</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ebookcentral.proquest.com/lib/hwr/detail.action?docID=6940009</subfield><subfield code="l">DE-2070s</subfield><subfield code="p">ZDB-30-PQE</subfield><subfield code="q">HWR_PDA_PQE</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| genre | (DE-588)4113937-9 Hochschulschrift gnd-content |
| genre_facet | Hochschulschrift |
| id | DE-604.BV048921028 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T21:55:16Z |
| indexdate | 2025-01-10T17:07:44Z |
| institution | BVB |
| isbn | 9783030966553 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034185119 |
| oclc_num | 1306273678 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 Online-Ressource (478 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Springer International Publishing AG |
| record_format | marc |
| series2 | Lecture Notes in Business Information Processing Series |
| spelling | Leemans, Sander J. J. Verfasser aut Robust Process Mining with Guarantees Process Discovery, Conformance Checking and Enhancement Cham Springer International Publishing AG 2022 ©2022 1 Online-Ressource (478 Seiten) txt rdacontent c rdamedia cr rdacarrier Lecture Notes in Business Information Processing Series v.440 Description based on publisher supplied metadata and other sources Intro -- Preface -- Acknowledgements -- Summary -- Contents -- 1 Introduction -- 1.1 Abstractions in Process Mining -- 1.2 Process Discovery -- 1.3 Conformance Checking -- 1.4 Enhancement & -- Tool Support -- 1.5 Contributions and Structure of this Book -- References -- 2 Preliminaries -- 2.1 Multisets, Traces, Regular Expressions -- 2.2 Process Models -- 2.2.1 Automata -- 2.2.2 Petri Nets -- 2.2.3 Yet Another Workflow Language -- 2.2.4 Business Process Model and Notation -- 2.2.5 Process Trees -- 2.3 Event Logs -- 2.3.1 Atomic Event Logs -- 2.3.2 Non-Atomic Event Logs -- 2.3.3 Richer Logs -- 2.4 Directly Follows Relation -- References -- 3 Process Mining -- 3.1 Different Use Cases, Different Process Mining Techniques -- 3.2 Formal Key Challenges of Process Mining -- 3.2.1 Models with Precise Semantics -- 3.2.2 System - Log - Model Relations -- 3.2.3 Simplicity & -- Balancing Log Criteria -- 3.2.4 An Ideal Technique (1) -- 3.3 Process Discovery -- 3.3.1 Discovery Algorithms Guaranteeing Soundness -- 3.3.2 Other Discovery Algorithms -- 3.3.3 An Ideal Process Discovery Technique (2) -- 3.4 Conformance Checking -- 3.4.1 Log Conformance Checking -- 3.4.2 System Conformance Checking -- 3.4.3 An Ideal Conformance Checking Technique (2) -- 3.5 Enhancement & -- Tool Support -- 3.5.1 Enhancements -- 3.5.2 Process Mining Tools -- 3.5.3 Requirements for Tool Support Beyond Process Discovery and Conformance Checking -- 3.6 Our Approach -- 3.6.1 A Process Discovery Framework -- 3.6.2 A Conformance Checking Framework -- 3.6.3 Enhancement & -- Tool Support -- 3.6.4 Future Work -- References -- 4 Recursive Process Discovery -- 4.1 Recursive Process Discovery -- 4.1.1 An Example of Recursive Process Discovery -- 4.1.2 The IM framework -- 4.1.3 More Technical Examples -- 4.1.4 Guarantees -- 4.2 Rediscoverability 4.2.1 Rediscoverability using Abstractions -- 4.2.2 Rediscoverability and the IM framework -- References -- 5 Abstractions -- 5.1 A Canonical Normal Form for Process Trees -- 5.1.1 Reduction Rules -- 5.1.2 Canonicity of the Reduction Rules -- 5.2 Language Uniqueness with Directly Follows Graphs -- 5.2.1 A Class of Trees: Cb -- 5.2.2 Footprints -- 5.2.3 Language Uniqueness -- 5.3 Language Uniqueness with Activity Relations -- 5.3.1 Activity Relations -- 5.3.2 Binary Trees -- 5.3.3 Language Uniqueness -- 5.4 Language Uniqueness with Interleaving -- 5.4.1 Footprint -- 5.4.2 A Class of Trees: Ci -- 5.4.3 Language Uniqueness -- 5.5 Language Uniqueness with Minimum Self-Distance -- 5.5.1 Minimum Self-Distance -- 5.5.2 A Class of Trees: Cm -- 5.5.3 Footprints -- 5.5.4 LC-Property -- 5.5.5 Language Uniqueness -- 5.6 Language Uniqueness with Optionality & -- Inclusive Choice -- 5.6.1 Optionality -- 5.6.2 Optionality in the Directly Follows Graph -- 5.6.3 A Class of Trees: Ccoo -- 5.6.4 Optionality under Sequence -- 5.6.5 Optionality under Inclusive Choice & -- Concurrency -- 5.6.6 Language Uniqueness -- 5.7 Language Uniqueness with non-Atomic Process Models -- 5.7.1 Non-Atomic Process Models -- 5.7.2 Representational Bias of Non-Atomic Models -- 5.7.3 Non-Atomic Directly Follows Graphs & -- Footprints -- 5.7.4 Concurrency Graphs & -- Footprints -- 5.7.5 A Class of Trees: Clc -- 5.7.6 Language Uniqueness -- 5.8 Classes of Process Trees: Revisited -- References -- 6 Discovery Algorithms -- 6.1 Inductive Miner (IM) -- 6.1.1 Example -- 6.1.2 Inductive Miner (IM) -- 6.1.3 Guarantees -- 6.2 Handling Deviating & -- Infrequent Behaviour -- 6.2.1 Deviating & -- Infrequent Behaviour -- 6.2.2 Inductive Miner - infrequent (IMf) -- 6.2.3 Example -- 6.2.4 Guarantees -- 6.3 Handling Incomplete Behaviour -- 6.3.1 Incomplete Behaviour 6.3.2 Inductive Miner - incompleteness (IMc) -- 6.3.3 Example -- 6.3.4 Guarantees -- 6.3.5 Finding Cuts: Translation to SMT -- 6.4 Handling More Constructs: , '39'42'"613A''45'47'"603A and '39'42'"613A''45'47'"603A -- 6.4.1 Example -- 6.4.2 Inductive Miner - all operators (IMa) -- 6.4.3 Inductive Miner - infrequent - all operators (IMfa) -- 6.4.4 Guarantees -- 6.5 Handling Non-Atomic Event Logs -- 6.5.1 Non-Atomic Event Logs -- 6.5.2 Inductive Miner - life cycle (IMlc) -- 6.5.3 Inductive Miner - infrequent - life cycle (IMflc) & -- Inductive Miner - incompleteness - life cycle (IMclc) -- 6.5.4 Implementation -- 6.5.5 Guarantees -- 6.6 Handling Large Event Logs -- 6.6.1 Example -- 6.6.2 Inductive Miner - directly follows based framework (IMd framework) -- 6.6.3 Inductive Miner - directly follows (IMd) -- 6.6.4 Inductive Miner - infrequent - directly follows (IMfd) -- 6.6.5 Inductive Miner - incompleteness - directly follows (IMcd) -- 6.6.6 Guarantees -- 6.7 Tool Support -- 6.8 Summary: Choosing a Miner -- References -- 7 Conformance Checking -- 7.1 Projected Conformance Checking Framework -- 7.1.1 Log to Projected Log to DFA -- 7.1.2 Model to Projected Model to DFA -- 7.1.3 Comparing DFAs & -- Measuring -- 7.1.4 Measuring over All Activities -- 7.2 An Example of Non-Conformance and Diagnostic Information -- 7.3 Guarantees -- 7.4 Tool Support -- 7.5 Conclusion -- 7.6 Ideas to Handle Unbounded & -- Weakly Unsound Petri Nets -- References -- 8 Evaluation -- 8.1 Evaluated Process Discovery Algorithms -- 8.2 Scalability of Discovery Algorithms -- 8.2.1 Set-up -- 8.2.2 Results -- 8.2.3 Discussion -- 8.3 Log-Quality Dimensions -- 8.3.1 Event Logs -- 8.3.2 Quantitative -- 8.3.3 Qualitative -- 8.3.4 Conclusion -- 8.4 Rediscoverability & -- its Challenges -- 8.4.1 Incomplete Behaviour -- 8.4.2 Deviating & -- Infrequent Behaviour 8.5 Evaluation of Log-Conformance Checking -- 8.5.1 Set-up -- 8.5.2 Results -- 8.5.3 Discussion -- 8.5.4 Evaluation Using the PCC framework -- 8.6 Non-Atomic Behaviour -- 8.6.1 Artificial Log -- 8.6.2 Real-Life Log -- 8.7 Conclusion -- References -- 9 Enhancement & -- Inductive visual Miner -- 9.1 Inductive visual Miner (IvM) -- 9.1.1 Steps & -- Architecture -- 9.1.2 Model Visualisation -- 9.1.3 Controls & -- Parameters -- 9.1.4 Adding Extensions -- 9.2 Deviations -- 9.2.1 Deviations and the PCC framework -- 9.2.2 Deviations and Alignments -- 9.3 Frequency Information -- 9.4 Projecting Performance Information on Process Trees -- 9.5 Animation -- 9.6 Conclusion -- References -- 10 Conclusion -- 10.1 Process Discovery -- 10.2 Conformance Checking -- 10.3 Enhancement & -- Tool Support -- 10.4 Remaining Challenges -- 10.4.1 Detailed -- 10.4.2 Future Work -- References -- Index Process mining Prozessanalyse Prozessmanagement (DE-588)4496282-4 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Prozessanalyse Prozessmanagement (DE-588)4496282-4 s DE-604 Erscheint auch als Druck-Ausgabe Leemans, Sander J. J. Robust Process Mining with Guarantees Cham : Springer International Publishing AG,c2022 9783030966546 |
| spellingShingle | Leemans, Sander J. J. Robust Process Mining with Guarantees Process Discovery, Conformance Checking and Enhancement Intro -- Preface -- Acknowledgements -- Summary -- Contents -- 1 Introduction -- 1.1 Abstractions in Process Mining -- 1.2 Process Discovery -- 1.3 Conformance Checking -- 1.4 Enhancement & -- Tool Support -- 1.5 Contributions and Structure of this Book -- References -- 2 Preliminaries -- 2.1 Multisets, Traces, Regular Expressions -- 2.2 Process Models -- 2.2.1 Automata -- 2.2.2 Petri Nets -- 2.2.3 Yet Another Workflow Language -- 2.2.4 Business Process Model and Notation -- 2.2.5 Process Trees -- 2.3 Event Logs -- 2.3.1 Atomic Event Logs -- 2.3.2 Non-Atomic Event Logs -- 2.3.3 Richer Logs -- 2.4 Directly Follows Relation -- References -- 3 Process Mining -- 3.1 Different Use Cases, Different Process Mining Techniques -- 3.2 Formal Key Challenges of Process Mining -- 3.2.1 Models with Precise Semantics -- 3.2.2 System - Log - Model Relations -- 3.2.3 Simplicity & -- Balancing Log Criteria -- 3.2.4 An Ideal Technique (1) -- 3.3 Process Discovery -- 3.3.1 Discovery Algorithms Guaranteeing Soundness -- 3.3.2 Other Discovery Algorithms -- 3.3.3 An Ideal Process Discovery Technique (2) -- 3.4 Conformance Checking -- 3.4.1 Log Conformance Checking -- 3.4.2 System Conformance Checking -- 3.4.3 An Ideal Conformance Checking Technique (2) -- 3.5 Enhancement & -- Tool Support -- 3.5.1 Enhancements -- 3.5.2 Process Mining Tools -- 3.5.3 Requirements for Tool Support Beyond Process Discovery and Conformance Checking -- 3.6 Our Approach -- 3.6.1 A Process Discovery Framework -- 3.6.2 A Conformance Checking Framework -- 3.6.3 Enhancement & -- Tool Support -- 3.6.4 Future Work -- References -- 4 Recursive Process Discovery -- 4.1 Recursive Process Discovery -- 4.1.1 An Example of Recursive Process Discovery -- 4.1.2 The IM framework -- 4.1.3 More Technical Examples -- 4.1.4 Guarantees -- 4.2 Rediscoverability 4.2.1 Rediscoverability using Abstractions -- 4.2.2 Rediscoverability and the IM framework -- References -- 5 Abstractions -- 5.1 A Canonical Normal Form for Process Trees -- 5.1.1 Reduction Rules -- 5.1.2 Canonicity of the Reduction Rules -- 5.2 Language Uniqueness with Directly Follows Graphs -- 5.2.1 A Class of Trees: Cb -- 5.2.2 Footprints -- 5.2.3 Language Uniqueness -- 5.3 Language Uniqueness with Activity Relations -- 5.3.1 Activity Relations -- 5.3.2 Binary Trees -- 5.3.3 Language Uniqueness -- 5.4 Language Uniqueness with Interleaving -- 5.4.1 Footprint -- 5.4.2 A Class of Trees: Ci -- 5.4.3 Language Uniqueness -- 5.5 Language Uniqueness with Minimum Self-Distance -- 5.5.1 Minimum Self-Distance -- 5.5.2 A Class of Trees: Cm -- 5.5.3 Footprints -- 5.5.4 LC-Property -- 5.5.5 Language Uniqueness -- 5.6 Language Uniqueness with Optionality & -- Inclusive Choice -- 5.6.1 Optionality -- 5.6.2 Optionality in the Directly Follows Graph -- 5.6.3 A Class of Trees: Ccoo -- 5.6.4 Optionality under Sequence -- 5.6.5 Optionality under Inclusive Choice & -- Concurrency -- 5.6.6 Language Uniqueness -- 5.7 Language Uniqueness with non-Atomic Process Models -- 5.7.1 Non-Atomic Process Models -- 5.7.2 Representational Bias of Non-Atomic Models -- 5.7.3 Non-Atomic Directly Follows Graphs & -- Footprints -- 5.7.4 Concurrency Graphs & -- Footprints -- 5.7.5 A Class of Trees: Clc -- 5.7.6 Language Uniqueness -- 5.8 Classes of Process Trees: Revisited -- References -- 6 Discovery Algorithms -- 6.1 Inductive Miner (IM) -- 6.1.1 Example -- 6.1.2 Inductive Miner (IM) -- 6.1.3 Guarantees -- 6.2 Handling Deviating & -- Infrequent Behaviour -- 6.2.1 Deviating & -- Infrequent Behaviour -- 6.2.2 Inductive Miner - infrequent (IMf) -- 6.2.3 Example -- 6.2.4 Guarantees -- 6.3 Handling Incomplete Behaviour -- 6.3.1 Incomplete Behaviour 6.3.2 Inductive Miner - incompleteness (IMc) -- 6.3.3 Example -- 6.3.4 Guarantees -- 6.3.5 Finding Cuts: Translation to SMT -- 6.4 Handling More Constructs: , '39'42'"613A''45'47'"603A and '39'42'"613A''45'47'"603A -- 6.4.1 Example -- 6.4.2 Inductive Miner - all operators (IMa) -- 6.4.3 Inductive Miner - infrequent - all operators (IMfa) -- 6.4.4 Guarantees -- 6.5 Handling Non-Atomic Event Logs -- 6.5.1 Non-Atomic Event Logs -- 6.5.2 Inductive Miner - life cycle (IMlc) -- 6.5.3 Inductive Miner - infrequent - life cycle (IMflc) & -- Inductive Miner - incompleteness - life cycle (IMclc) -- 6.5.4 Implementation -- 6.5.5 Guarantees -- 6.6 Handling Large Event Logs -- 6.6.1 Example -- 6.6.2 Inductive Miner - directly follows based framework (IMd framework) -- 6.6.3 Inductive Miner - directly follows (IMd) -- 6.6.4 Inductive Miner - infrequent - directly follows (IMfd) -- 6.6.5 Inductive Miner - incompleteness - directly follows (IMcd) -- 6.6.6 Guarantees -- 6.7 Tool Support -- 6.8 Summary: Choosing a Miner -- References -- 7 Conformance Checking -- 7.1 Projected Conformance Checking Framework -- 7.1.1 Log to Projected Log to DFA -- 7.1.2 Model to Projected Model to DFA -- 7.1.3 Comparing DFAs & -- Measuring -- 7.1.4 Measuring over All Activities -- 7.2 An Example of Non-Conformance and Diagnostic Information -- 7.3 Guarantees -- 7.4 Tool Support -- 7.5 Conclusion -- 7.6 Ideas to Handle Unbounded & -- Weakly Unsound Petri Nets -- References -- 8 Evaluation -- 8.1 Evaluated Process Discovery Algorithms -- 8.2 Scalability of Discovery Algorithms -- 8.2.1 Set-up -- 8.2.2 Results -- 8.2.3 Discussion -- 8.3 Log-Quality Dimensions -- 8.3.1 Event Logs -- 8.3.2 Quantitative -- 8.3.3 Qualitative -- 8.3.4 Conclusion -- 8.4 Rediscoverability & -- its Challenges -- 8.4.1 Incomplete Behaviour -- 8.4.2 Deviating & -- Infrequent Behaviour 8.5 Evaluation of Log-Conformance Checking -- 8.5.1 Set-up -- 8.5.2 Results -- 8.5.3 Discussion -- 8.5.4 Evaluation Using the PCC framework -- 8.6 Non-Atomic Behaviour -- 8.6.1 Artificial Log -- 8.6.2 Real-Life Log -- 8.7 Conclusion -- References -- 9 Enhancement & -- Inductive visual Miner -- 9.1 Inductive visual Miner (IvM) -- 9.1.1 Steps & -- Architecture -- 9.1.2 Model Visualisation -- 9.1.3 Controls & -- Parameters -- 9.1.4 Adding Extensions -- 9.2 Deviations -- 9.2.1 Deviations and the PCC framework -- 9.2.2 Deviations and Alignments -- 9.3 Frequency Information -- 9.4 Projecting Performance Information on Process Trees -- 9.5 Animation -- 9.6 Conclusion -- References -- 10 Conclusion -- 10.1 Process Discovery -- 10.2 Conformance Checking -- 10.3 Enhancement & -- Tool Support -- 10.4 Remaining Challenges -- 10.4.1 Detailed -- 10.4.2 Future Work -- References -- Index Process mining Prozessanalyse Prozessmanagement (DE-588)4496282-4 gnd |
| subject_GND | (DE-588)4496282-4 (DE-588)4113937-9 |
| title | Robust Process Mining with Guarantees Process Discovery, Conformance Checking and Enhancement |
| title_auth | Robust Process Mining with Guarantees Process Discovery, Conformance Checking and Enhancement |
| title_exact_search | Robust Process Mining with Guarantees Process Discovery, Conformance Checking and Enhancement |
| title_exact_search_txtP | Robust Process Mining with Guarantees Process Discovery, Conformance Checking and Enhancement |
| title_full | Robust Process Mining with Guarantees Process Discovery, Conformance Checking and Enhancement |
| title_fullStr | Robust Process Mining with Guarantees Process Discovery, Conformance Checking and Enhancement |
| title_full_unstemmed | Robust Process Mining with Guarantees Process Discovery, Conformance Checking and Enhancement |
| title_short | Robust Process Mining with Guarantees |
| title_sort | robust process mining with guarantees process discovery conformance checking and enhancement |
| title_sub | Process Discovery, Conformance Checking and Enhancement |
| topic | Process mining Prozessanalyse Prozessmanagement (DE-588)4496282-4 gnd |
| topic_facet | Process mining Prozessanalyse Prozessmanagement Hochschulschrift |
| work_keys_str_mv | AT leemanssanderjj robustprocessminingwithguaranteesprocessdiscoveryconformancecheckingandenhancement |