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Titlebook: Business Process Management Workshops; BPM 2016 Internation Marlon Dumas,Marcelo Fantinato Conference proceedings 2017 Springer Internation

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發(fā)表于 2025-3-21 16:20:32 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Business Process Management Workshops
期刊簡(jiǎn)稱BPM 2016 Internation
影響因子2023Marlon Dumas,Marcelo Fantinato
視頻videohttp://file.papertrans.cn/193/192370/192370.mp4
發(fā)行地址Includes supplementary material: .Includes supplementary material:
學(xué)科分類Lecture Notes in Business Information Processing
圖書封面Titlebook: Business Process Management Workshops; BPM 2016 Internation Marlon Dumas,Marcelo Fantinato Conference proceedings 2017 Springer Internation
影響因子.This book constitutes the revised papers of the ten international workshops that were held at BPM 2016, the 14.th. International Conference on Business Process Management, held in Rio de Janeiro, Brazil, in September 2016. . . The 36 papers included in this volume were carefully reviewed and selected from a total of 64 submissions. They are from the following workshops: .BPI 2016. – 12th International Workshop on Business Process Intelligence; .BPMO 2016. – 1st Workshop on Workshop on Business Process Management and Ontologies; .BPMS2 2016. – 9th Workshop on Social and Human Aspects of Business Process Management; .DeMiMoP 2016. – 4th International Workshop on Decision Mining & Modeling for Business Processes; .IWPE 2016. – 2nd International Workshop on Process Engineering; .PQ 2016. – 1st International Workshop on Process Querying; .ReMa 2016. – 1st Workshop on Resource Management in Business Processes; .PRAISE 2016. – 1stInternational Workshop on Runtime Analysis of Process-Aware Information Systems; .SABPM 2016. – 1st International Workshop on Sustainability-Aware Business Process Management; .TAProViz 2016. – 5th International Workshop on Theory and Application of Visualizatio
Pindex Conference proceedings 2017
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A Framework for Interactive Multidimensional Process Mining split the event log into a set of homogenous sublogs according to its case and event attributes. Process mining techniques are used to create an individual process model for each sublog representing variants of the process. These models can be compared to identify the differences between the varian
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Multi-objective Trace Clustering: Finding More Balanced Solutionsg their solution based on a certain type of similarity between the traces, such as the number of insertions and deletions needed to transform one trace into another; by mapping the traces onto a vector space model, based on certain patterns in each trace; or on the quality of a process model discove
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Simulation of Multi-perspective Declarative Process Modelsge. Process mining techniques can be used to automate the discovery of process models. One way to evaluate process mining techniques is to synthesize event logs from a source model via simulation techniques and to compare the discovered model with the source model. Though there are several declarati
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PROMPTUM Toolset: Tool Support for Integrated Ontologies and Process Modelsaging the relationships between ontologies and business process models provide benefits such as enhanced semantic quality of both artifacts and effort savings. In this study, the PROMPTUM toolset, that enables to model relations between the ontologies and the labels within the process model collecti
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Ontology-Based Heuristics for Process Behavior: Formalizing False Positive Scenarioshe latter are based on heuristics. The main advantage of informal methods with respect to the formal ones is their short run-time. However, heuristics may lead to false positives, i.e. they may detect errors in a process model even though such model is correct. In this work, we propose using ontolog
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