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A Generic Framework for Attribute-Driven Hierarchical Trace Clustering · Study

WorkA Generic Framework for Attribute-Driven Hierarchical Trace Clustering

Sebastiaan J. van Zelst2020

Work2020

A Generic Framework for Attribute-Driven Hierarchical Trace Clustering

Sebastiaan J. van Zelst · Yukun Cao

15 citations·0/0 files stored·Lecture notes in business information processing

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Business Process Modeling and Analysis Data Mining Algorithms and Applications Software System Performance and Reliability

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2016Data Science in Action 2018Automated Discovery of Process Models from Event Logs: Review and Benchmark 2009Trace Clustering in Process Mining 2006Discovering expressive process models by clustering log traces 2009Context Aware Trace Clustering: Towards Improving Process Mining Results 2013Active Trace Clustering for Improved Process Discovery 2016Filtering Out Infrequent Behavior from Business Process Event Logs 2010Trace Clustering Based on Conserved Patterns: Towards Achieving Better Process Models

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2015A Comparative Analysis of Process Instance Cluster Techniquesarticle · 9 shared references 2020A Generic Framework for Trace Clustering in Process Miningother · 8 shared references 2022Complex Process Modeling in Process Mining: A Systematic Reviewreview · 8 shared references 2019Scalable Mixed-Paradigm Trace Clustering using Super-Instancesother · 8 shared references 2016Explaining clusterings of process instancesarticle · 7 shared references 2017Alignment-Based Trace Clusteringother · 7 shared references

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Year2020

Typeother

Published2020-01-01

VenueLecture notes in business information processing

ISSN-L1865-1348

Languageen

Citations15

Files0 public / 0

ShelfBusiness Process Modeling and Analysis

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doi10.1007/978-3-030-66498-5_23

openalex_workW3121962896

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