Looking into the TESSERACT: Time-drifts in event streams using series of evolving rolling averages of completion times-Reference-Cited by-同舟云学术

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Looking into the TESSERACT: Time-drifts in event streams using series of evolving rolling averages of completion times

Published:2019-09 Issue: Volume:84 Page:265-282
ISSN:0306-4379
Container-title:Information Systems
language:en
Short-container-title:Information Systems

Author:

Richter Florian,Seidl Thomas

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Software

Reference43 articles.

1. Dealing with concept drifts in process mining;Bose;IEEE Trans. Neural Netw. Learn. Syst.,2014

2. Handling concept drift in process mining;Bose,2011

3. Online techniques for dealing with concept drift in process mining;Carmona,2012

4. Andrea Burattin, Alessandro Sperduti, Wil MP van der Aalst, Heuristics miners for streaming event data, 2012. arXiv:1212.6383.

5. Control-flow discovery from event streams;Burattin,2014

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1. Detecting Process Duration Drift Using Gamma Mixture Models in a Left-Truncated and Right-Censored Environment;ACM Transactions on Knowledge Discovery from Data;2024-08-21

2. A survey of approaches for event sequence analysis and visualization;Information Systems;2024-02

3. Integrated detection and localization of concept drifts in process mining with batch and stream trace clustering support;Data & Knowledge Engineering;2024-01

4. Causal Graph: Interpretation of Causal Relationships in Temporary Deviations of Business Processes;2023 XLIX Latin American Computer Conference (CLEI);2023-10-16

5. A Survey on Concept Drift in Process Mining;ACM Computing Surveys;2022-12-31

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