Business Process Management

Name: Business Process Management | 13th International Conference, BPM 2015, Innsbruck, Austria, August 31 -- September 3, 2015, Proceedings
Brand: Springer
Price: 53.49 EUR
Availability: OnlineOnly

13th International Conference, BPM 2015, Innsbruck, Austria, August 31 -- September 3, 2015, Proceedings

Hamid Reza Motahari-Nezhad Jan Recker Matthias Weidlich(Herausgeber*in)

Springer (Verlag)

Erschienen am 12. August 2015

XXIV, 476 Seiten

E-Book

PDF mit Wasserzeichen-DRM

Systemvoraussetzungen

978-3-319-23063-4 (ISBN)

53,49 €inkl. 7% MwSt.

Systemvoraussetzungen

für PDF mit Wasserzeichen-DRM

E-Book Einzellizenz

Als Download verfügbar

Beschreibung

Weitere Details

Weitere Ausgaben

Inhalt

Intro
Preface
Organization
Keynotes
From Models to Data and Back: The Journeyof the BPM Discipline and the Tangled Roadto BPM 2020
NoBPM: Supporting Interaction-OrientedAutomation via Normative Specificationsof Processes
Adaptability, Architecture and CX:The Bizagi Way
Contents
Runtime Process Management
Improving Business Processes: Does Anybody have an Idea?
1 Introduction
2 Background
3 Hypotheses
4 Research Method
5 Results
5.1 Results Hypotheses Testing
5.2 Results Follow-Up Analysis
6 Discussion
7 Related Work
8 Conclusion
References
Inspection Coming Due! How to Determine the Service Interval of Your Processes!
1 Introduction
2 Theoretical Background
2.1 Business Process Monitoring and Controlling
2.2 Process Performance Management and Value-Based BPM
2.3 Predicting Process Performance Using Stochastic Processes
3 The Critical Process Instance Method
3.1 General Setting
3.2 The Role of Variation and Deviance
3.3 Determining the Critical Process Instance
3.4 Integration into the BPM Lifecycle
4 Demonstration Example
5 Discussion
6 Conclusion
References
Data-Driven Performance Analysis of Scheduled Processes
1 Introduction
2 Approach Overview
3 Models
4 Discovery of Queue-Enabling CSPN Models
5 Folding and Projection of QCSPN into Queueing Networks
5.1 Folding of QCSPN
5.2 Projection of QCSPN into Queueing Networks.
6 Evaluation
7 Related Work
8 Conclusion
References
Process Modeling
Specification and Verification of Complex Business Processes - A High-Level Petri Net-Based Approach
1 Introduction
2 Related Work
3 Background
3.1 BPMN Overview
3.2 RECATNet Overview
4 RECATNet Based Model Verification for Business Processes
5 Mapping BPMN into RECATNets
5.1 Mapping Events and Gateways
5.2 Mapping Activities
5.3 Exception Handling
5.4 Cancellation Activity
6 Case Studies
6.1 Travel Request Process
6.2 Intelligence Test Process (Cancel Multiple Instance Activity)
7 Formal Semantics of the Mapping BPMN into RECATNet
8 Conclusion and Future Work
References
Concurrency and Asynchrony in Declarative Workflows
1 Introduction
2 Concurrency and Declarative Workflows
2.1 A Mortgage Credit Application Workflow
2.2 A DCR Formalisation
2.3 Concurrency in the Example Workflow
3 DCR Graphs
4 Asynchronous Transition Systems and DCR Graphs
5 A Process Engine for Distributed Declarative Workflows
6 Conclusion
6.1 Discussion and Future Work
References
Detecting Inconsistencies Between Process Models and Textual Descriptions
1 Introduction
2 Problem Illustration
3 Related Work
4 Approach
4.1 Overview
4.2 Linguistic Analysis
4.3 Computation of Similarity Scores
4.4 Optimal Correspondence Relation
4.5 Inconsistency Assessment
5 Evaluation
5.1 Test Collection
5.2 Setup
5.3 Results
5.4 Discussion
6 Conclusions
References
Process Model Discovery I
Mining Invisible Tasks in Non-free-choice Constructs
1 Introduction
2 A Motivating Example
3 Preliminaries
3.1 Event Log
3.2 Workflow Net
4 The New Mining Algorithm $
4.1 Basic Relations
4.2 Detecting Invisible Tasks by Improved Mendacious Dependency
4.3 Complementing Reachable Dependencies
4.4 Detecting Non-free-choice Constructs
4.5 Adjusting Invisible Tasks
Combining Invisible Tasks.
Splitting Invisible Tasks.
4.6 The $ Algorithm
5 Experimental Evaluation
5.1 Evaluation Based on Artificial Logs
5.2 Evaluation Based on Real-Life Log
6 Conclusion and Future Work
References
Incorporating Negative Information in Process Discovery
1 Introduction
2 Preliminaries
2.1 Parikh Representation of an Event Log
2.2 Petri Nets and Process Discovery
2.3 Convex Polyhedra and Integer Lattices
2.4 Numerical Abstract Domains and Process Discovery
2.5 Inducing Negative Information from a Log or Model
3 Supervised Process Discovery
3.1 Stages of the Approach
3.2 Generalization and Simplification on the Positive Perspective
3.3 Improving Generalization and Simplicity via Negative Information
3.4 Discussion
4 Supervising Arbitrary Process Discovery Techniques
5 Experiments
5.1 Supervising Process Discovery Techniques
5.2 Empirical Comparison
6 Related Work
7 Conclusions and Future Work
References
Ensuring Model Consistency in Declarative Process Discovery
1 Introduction
2 Background
2.1 The Consistency Problem
2.2 The Minimality Problem
3 Framing the Problem
4 The Approach
4.1 Declare Models as Automata
4.2 The Algorithm
5 Experiments and Results
6 Related Work
7 Conclusion
References
Business Process Models and Analytics
Avoiding Over-Fitting in ILP-Based Process Discovery
1 Introduction
2 Motivation
3 Exceptional Behavior and ILP-Based Discovery
4 Sequence Encoding
5 Sequence Encoding Filtering
6 Evaluation
7 Conclusion
References
Estimation of Average Latent Waiting and Service Times of Activities from Event Logs
1 Introduction
2 Related Work
3 Performance Indicators of Activities Deliverable from Event Logs
4 Probabilistic Model
5 Estimation of Parameters
6 Experimental Results
6.1 Synthetic Log
6.2 Teleclaim Log
7 Conclusion
References
A Structural Model Comparison for Finding the Best Performing Models in a Collection
1 Introduction
2 Model Collection
3 Throughput Time
3.1 At-Least-as-Good Runs
3.2 At-Least-as-Good Models
4 Related Work
5 Conclusion
References
Context-Sensitive Textual Recommendations for Incomplete Process Model Elements
1 Introduction
2 Problem Illustration
3 Conceptual Approach
4 Evaluation
5 Related Work
6 Conclusion
References
Extracting Configuration Guidance Models from Business Process Repositories
1 Introduction
2 Configuration Guidance Model
3 Deriving Configuration Guidance Models
3.1 Extracting Tree Hierarchy
3.2 Deriving Additional Model Information
4 Related Work
5 Conclusion and Future Works
References
BPM in Industry
Web-Based Modelling and Collaborative Simulation of Declarative Processes
1 Introduction
1.1 Related Work
2 Hierarchical DCR Graphs
3 The DCR Graphs Process Portal
4 Development of the DCR Portal
5 Evaluation
6 Future Work
7 Conclusion
References
Case Analytics Workbench: Platform for Hybrid Process Model Creation and Evolution
1 Introduction
2 Related Work
3 Case Analytics Workbench
3.1 Case Model Definition
3.2 Data Management and Clustering
3.3 Process Mining
3.4 Evidence Management Module
4 Case Studies
4.1 Case Study 1: Und derwriting Process Creation and Derivation
4.2 Case Study 2: Care Pathway Refinement
5 Discussion and Conclusion
References
A Clinical Pathway Mining Approach to Enable Scheduling of Hospital Relocations and Treatment Services
1 Introduction
2 Related Work
3 Concept of Scheduling-Focused Clinical Pathways
4 Pathway Mining Approach
5 Results
6 Conclusion
References
A Framework for Benchmarking BPMN 2.0 Workflow Management Systems
1 Introduction
2 Related Work
3 The BenchFlow Benchmarking Framework
3.1 Performance Test Execution
3.2 Performance Analyzes
4 Evaluation: Preliminary Scalability Experiment
4.1 Experiment Description and Set-Up
4.2 Results
5 Conclusion and Future Work
References
Process Compliance and Deviations
Visually Monitoring Multiple Perspectives of Business Process Compliance
1 Introduction
2 Fundamentals
3 eCRG Compliance Monitoring
4 Evaluation
5 Related Work
6 Summary and Outlook
References
Managing Controlled Violation of Temporal Process Constraints
1 Introduction
2 Modeling Approach
2.1 A Simple Temporal Model
2.2 Structural Constraints (SC)
2.3 Additional Temporal Constraints
3 Building and Solving the Constraint Satisfaction Model
3.1 Design Time Solution
3.2 Run-Time Solution
4 Model for Temporal Constraint Violations
4.1 Relaxation Variables
4.2 Controlled Violation with Penalties
4.3 Associating Penalties with Slack Variables
5 Further Extensions
5.1 Overlap Patterns
5.2 Repetition Patterns
6 Discussion and Related Work
7 Conclusions
References
Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes
1 Introduction
2 Background and Related Work
2.1 Predictive Monitoring: The Related Work
2.2 Hidden Markov Models
3 Predictive Monitoring: The Proposed Approach
3.1 Overview
3.2 Complex Symbolic Sequence Encodings
3.3 Baselines
3.4 Index-Based Encoding
3.5 HMM-Based Encoding
4 Evaluation
4.1 Datasets
4.2 Evaluation Measures
4.3 Evaluation Procedure
4.4 Results and Discussion
5 Conclusion
References
Emerging and Practical Areas of BPM
Business Process Management Skills and Roles: An Investigation of the Demand and Supply Side of BPM Professionals
1 Introduction
2 Data Collection and Analysis
2.1 Sampling of Advertised BPM Positions
2.2 Sampling of Profiles of BPM Professionals
3 Process Roles and Skills Demanded by Industry
3.1 The Chief Process Officer
3.2 The Process Architect
3.3 The Process Consultant
3.4 The Process Analyst
4 Profiles of BPM Professionals on the Market
4.1 The Chief Process Officer
4.2 The Process Owner
4.3 The Process Architect
4.4 The Process Consultant
4.5 The Process Analyst
5 Discussion and Conclusion
5.1 Insights for Practice
5.2 Limitations and Future Research
References
BPMN Task Instance Streaming for Efficient Micro-task Crowdsourcing Processes
1 Introduction
2 Crowdsourcing Processes
2.1 Scenario: Transcription of Receipts
2.2 Crowdsourcing Processes and Streaming Opportunities
3 Assumptions and Approach
4 Streaming Crowd Tasks
4.1 Modeling Micro-task Instance Streaming
4.2 Model Transformation
4.3 Runtime Environment
5 Case Study and Evaluation
5.1 Modeling and Implementation
5.2 Performance Evaluation
6 Related Work
7 Conclusion
References
Goal-Aligned Categorization of Instance Variants in Knowledge-Intensive Processes
1 Introduction
1.1 Preliminaries
1.2 Key Contributions
2 Running Example
3 Goal-Driven Variant Mining
4 Evaluation
5 Related Work
6 Conclusion
References
Process Monitoring
Process Mining on Databases: Unearthing Historical Data from Redo Logs
1 Introduction
2 Walkthrough
2.1 Event Extraction
2.2 Exploiting the Data Model
2.3 Process Instance Identification
3 Formalizations
4 Implementation
5 Demonstration
5.1 Which are the Steps Followed by a User to Book a Ticket?
5.2 Could Customers Book Tickets Before all the Bands were Confirmed?
5.3 Do Bands Ever Cancel Their Performance in Concerts?
5.4 Are Venues Being Reserved Before or After the Bands have Confirmed Their Performance?
6 Conclusion
References
Log Delta Analysis: Interpretable Differencing of Business Process Event Logs
1 Introduction
2 Background and Related Work
2.1 Deviance Mining
2.2 Event Structures
3 Constructing Event Structures from Logs
4 Comparing Event Structures
4.1 Control-Flow Comparison
4.2 Frequency-Enhanced Comparison
5 Evaluation
5.1 Evaluation on Synthetic Logs
5.2 Evaluation on Real-Life Logs
6 Conclusion
References
Fast and Accurate Business Process Drift Detection
1 Introduction
2 Related Work
3 Drift Detection Method
3.1 From Event Logs to Partial Order Runs
3.2 Statistical Testing Over Runs
3.3 Adaptive Window
4 Evaluation on Synthetic Logs
4.1 Setup
4.2 Impact of Window Size on Accuracy
4.3 Impact of Adaptive Window Size on Accuracy
4.4 Accuracy Per Change Pattern
4.5 Execution Times
4.6 Comparison with Baseline
5 Evaluation on Real-Life Log
6 Conclusion
References
Process Model Discovery II
Mining Project-Oriented Business Processes
1 Introduction
2 Background
2.1 Problem Description
2.2 Related Work
3 Mining VCS Event Data
3.1 Preliminaries
3.2 Project Discovery Technique
Step 1: Preprocessing.
Step 2: Aggregating events to activities.
Steps 3 and 4: Mapping activities to work packages and aggregating.
Step 5: Computing work package characteristics.
4 Evaluation
4.1 Experimental Setup
4.2 Input Data Description
4.3 Output Data
4.4 Project Analysis
4.5 Coverage Tests on Available Open Projects
5 Discussion
6 Conclusion
References
Efficient Process Model Discovery Using Maximal Pattern Mining
1 Introduction
2 Background and Related Work
3 Maximal Pattern Mining (MPM)
3.1 Overview
3.2 Generating Maximal Patterns
3.3 Assumptions and Limitations
4 Experimental Result
4.1 Criteria
5 Conclusion and Future work
References
Log-Based Simplification of Process Models
1 Introduction
1.1 Motivating Example
2 Preliminaries
2.1 Process Models
2.2 Process Mining
3 Overview of Proposed Simplification Techniques
4 Log-Based Arc Scores
5 Simplification Techniques Using Log-Based Scores
5.1 Simplification to a Series-Parallel Net
5.2 Simplification Using ILP Models
6 Simplification by Projection into Structural Classes
6.1 Free Choice
6.2 State Machine
7 Experimental Evaluation
7.1 Comparison of the Different Simplification Techniques
7.2 Effect of the Threshold Parameter on the ILP Model
8 Related Work
9 Conclusions
References
Author Index

Systemvoraussetzungen

Als PDF speichern Als Link merken