Correlation Analysis of TLRA with Log-System Recall and Species-Discovery Coverage: A Comparative Evaluation Dataset
收藏DataCite Commons2025-08-04 更新2025-04-17 收录
下载链接:
https://figshare.unimelb.edu.au/articles/dataset/Correlation_Data_for_Species-Coverage-based_Log_Representativeness_and_TLRA/26410747/2
下载链接
链接失效反馈官方服务:
资源简介:
This dataset supports the study of correlations between <b>Trace-based Log Representativeness Approximation (TLRA)</b> and two measures: log-system recall (ground truth alignment) and species-discovery-based coverage. The analysis was conducted across event logs of 60 generative systems and varying log sizes and noise levels.<b>Version 1</b>: Focuses on the correlation analysis between TLRA and species-discovery-based coverage (as presented in ieeexplore.ieee.org/document/10680679).<b>Version 2</b>: Extends the analysis by incorporating a ground truth evaluation through log-system recall.The systems and logs used for this analysis are available for download in our GitHub repository.We kindly request that you cite our work if you use this dataset in your research:<br><i>A. Karunaratne, A. Polyvyanyy, and A. Moffat, “The role of log representativeness in estimating </i><i>generalization in process mining,” in Int. Conf. Process Mining. IEEE, 2024, pp. 33-40.</i>
提供机构:
The University of Melbourne
创建时间:
2024-12-11



