Simultaneous Process Drift Detection and Characterization with Pattern-Based Change Detectors
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-61527-7_30
Reference17 articles.
1. van der Aalst, W.M.P., Weijters, T., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16(9), 1128–1142 (2004). https://doi.org/10.1109/TKDE.2004.47
2. Assy, N., van Dongen, B.F., van der Aalst, W.M.P.: Discovering hierarchical consolidated models from process families. Adv. Inf. Syst. Eng. - CAiSE 2017, 314–329 (2017). https://doi.org/10.1007/978-3-319-59536-8_20
3. Bifet, A., Gavaldà, R.: Learning from time-changing data with adaptive windowing. In: Proceedings of the Seventh SIAM International Conference on Data Mining, pp. 443–448 (2007).https://doi.org/10.1137/1.9781611972771.42
4. Bose, R.P.J.C., van der Aalst, W.M.P., Zliobaite, I., Pechenizkiy, M.: Handling concept drift in process mining. In: Advances Information Systems Engineering, pp. 391–405 (2011). https://doi.org/10.1007/978-3-642-21640-4_30
5. Bose, R.P.J.C., van der Aalst, W.M.P., Zliobaite, I., Pechenizkiy, M.: Dealing with concept drifts in process mining. IEEE Trans. Neural Networks Learn. Syst. 25(1), 154–171 (2014). https://doi.org/10.1109/TNNLS.2013.2278313
Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Revisiting the Transition Matrix-Based Concept Drift Approach: Improving the Detection Task Reliability Through Additional Experimentation;SN Computer Science;2024-01-10
2. Adaptive Bernstein change detector for high-dimensional data streams;Data Mining and Knowledge Discovery;2024-01-09
3. Integrated detection and localization of concept drifts in process mining with batch and stream trace clustering support;Data & Knowledge Engineering;2024-01
4. An Experimental Evaluation of Process Concept Drift Detection;Proceedings of the VLDB Endowment;2023-04
5. A Survey on Concept Drift in Process Mining;ACM Computing Surveys;2022-12-31
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3