Using contextualized activity-level duration to discover irregular process instances in business operations-Reference-Cited by-同舟云学术

Using contextualized activity-level duration to discover irregular process instances in business operations

Published:2017-06 Issue: Volume:391-392 Page:80-98
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Hsu Ping-Yu,Chuang Yu-Cheng,Lo Yao-Chung,He Shuang-Chuan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference50 articles.

1. A survey of anomaly detection techniques in financial domain;Ahmed;Future Gen. Comput. Syst.,2016

2. Functionality and limitations of current workflow management systems;Alonso;IEEE Exp.,1997

3. A novel secure business process modeling approach and its impact on business performance;Alotaibi;Inf. Sci.,2014

4. Exploiting domain knowledge to detect outliers;Angiulli;Data Mining Knowl. Discov.,2014

5. Planning of business process execution in business process management environments;Bae;Inf. Sci.,2014

Cited by 19 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. A business process network efficiency model for handling conflicting information;Knowledge-Based Systems;2024-06

2. Business Process Anomaly Detection and Root Cause Analysis Using BLSTM-VAE With Attention;IEEE Access;2024

3. GRASPED: A GRU-AE Network Based Multi-Perspective Business Process Anomaly Detection Model;IEEE Transactions on Services Computing;2023-09

4. Optimal event log sanitization for privacy-preserving process mining;Data & Knowledge Engineering;2023-05

5. Deep reinforcement learning for data-efficient weakly supervised business process anomaly detection;Journal of Big Data;2023-03-12