Path：Home>Scientific Research>Research Achievement
Scientific Research
Processing of event data
2021-12-23
Content of result
Event Data Quality Control：Aiming at the problems of event loss, disorder, label error, and structure error in multi-source event logs, study the efficient filtering and repair mechanism of each track in the event log under the guidance of the correct process model；Aiming at the problem of inconsistency between the event trajectory and the process model caused by the process change caused by the dynamic and changeable process execution environment, research on the automatic repair technology of the original process model with the minimum cost based on the correct event log；Research in this area also includes stream data cleaning techniques based on speed constraints.
Event Data Integration and Management：For the rapidly growing event sequence data and process models with process characteristics from all walks of life,Research on key processing such as efficient integration, unified storage, feature extraction, similarity calculation, difference calculation, classification and clustering, multi-dimensional indexing and comprehensive retrieval of multi-source, heterogeneous, massive event logs (also known as process instance logs) and process models Technology. Combined with the big data processing platform, the distributed parallel acceleration algorithm of the above technology is studied, which lays a solid application foundation for the management, analysis and reuse of event data.
Process data analysis and mining:Develop parallelization techniques (T1) that decompose process mining problems into multiple smaller mining problems distributed to computer clusters; for applications that cannot store all events for a very long period of time, develop incremental learning processes without storing all events Just-in-time process mining techniques for models (T2); develop comparable process mining techniques that systematically highlight commonalities and differences in order to be able to handle heterogeneous processes that change over time and have many variants (T3).
Research results
- Jianmin Wang, Shaoxu Song, Xuemin Lin, Xiaochen Zhu, Jian Pei. Cleaning Structured Event Logs: A Graph Repair Approach. IEEE International Conference on Data Engineering, ICDE 2015
- Shaoxu Song, Aoqian Zhang, Jianmin Wang, Philip S. Yu. SCREEN: Stream Data Cleaning under Speed Constraints. ACM SIGMOD International Conference on Management of Data, SIGMOD 2015
- Xiaochen Zhu, Shaoxu Song, Xiang Lian, Jianmin Wang, Lei Zou. Matching Heterogeneous Event Data. ACM SIGMOD International Conference on Management of Data, SIGMOD 2014: 1211-1222
- Xiaochen Zhu, Shaoxu Song, Jianmin Wang, Philip S. Yu, Jiaguang Sun. Matching Heterogeneous Events with Patterns. IEEE International Conference on Data Engineering, ICDE 2014: 376-387
- Tao Jin, Jianmin Wang, Yun Yang, Lijie Wen, Keqin Li. Refactor Business Process Models with Maximized Parallelism. IEEE Transactions on Services Computing, 2014
- Tao Jin, Jianmin Wang, Lijie Wen, Gen Zou. Computing Refined Ordering Relations with Uncertainty for Acyclic Process Models. IEEE Transactions on Services Computing, 2014
- Jianmin Wang, Tao Jin, Raymond K. Wong, Lijie Wen. Querying business process model repositories - A survey of current approaches and issues. World Wide Web, 2014
- Hedong Yang, Lijie Wen, Jianmin Wang, Raymond K. Wong. CPL+: An improved approach for evaluating the local completeness of event logs. Information Processing Letters, 2014
- Jianmin Wang, Shaoxu Song, Xiaochen Zhu, Xuemin Lin. Efficient Recovery of Missing Events. Proceedings of the VLDB Endowment, PVLDB 6(10): 841-852 (2013)
- Tao Jin, Jianmin Wang, Marcello La Rosa, Arthur H. M. ter Hofstede, Lijie Wen. Efficient querying of large process model repositories. Computers in Industry, 2013
- Jianmin Wang, Raymond K. Wong, Jianwei Ding, Qinlong Guo, Lijie Wen. Efficient Selection of Process Mining Algorithms. IEEE Transactions on Services Computing, 2013
- Liang Song, Jianmin Wang, Lijie Wen, Hui Kong. Efficient Semantics-Based Compliance Checking Using LTL Formulae and Unfolding. Journal of Applied Mathematics, 2013
- Zhaoxia Wang, Jianmin Wang, Xiaochen Zhu, Lijie Wen. Verification of workflow nets with transition conditions. Journal of Zhejiang University - Science C, 2012
- Haiping Zha, Wil M. P. van der Aalst, Jianmin Wang, Lijie Wen, Jiaguang Sun. Verifying workflow processes: a transformation-based approach. Software and System Modeling, 2011
- Haiping Zha, Jianmin Wang, Lijie Wen, Chaokun Wang, Jiaguang Sun. A workflow net similarity measure based on transition adjacency relations. Computers in Industry, 2010
- Lijie Wen, Jianmin Wang, Wil M. P. van der Aalst, Biqing Huang, Jiaguang Sun. Mining process models with prime invisible tasks. Data & Knowledge Engineering, 2010
- Lijie Wen, Jianmin Wang, Wil M. P. van der Aalst, Biqing Huang, Jiaguang Sun. A novel approach for process mining based on event types. Journal of Intelligent Information Systems, 2009
- Lijie Wen, Wil M. P. van der Aalst, Jianmin Wang, Jiaguang Sun. Mining process models with non-free-choice constructs. Data Mining and Knowledge Discovery, 2007
- 殷明; 闻立杰; 王建民; 查海平; 刘英博; 董子禾. 一种器械设备的工作状态检测方法，2014/05/27. 清华大学，专利，申请号：201410225173.3
- 流程数据管理与分析挖掘软件 V1.0，清华大学，软件著作权，登记号：2014SR190808
- 流程模式及片段优化分析工具软件 V1.0，清华大学，软件著作权，登记号：2014SR190823
- 在线数据流程管理平台 V1.0，清华大学，软件著作权，登记号：2014SR190811
- 流程数据管理与分析挖掘软件 V1.0，清华大学，软件著作权，登记号：2014SR190808
