{"title":"Process Mining of Duplicate Tasks: A Systematic Literature Review","authors":"Chenchen Duan, Qingjie Wei","doi":"10.1109/ICAICA50127.2020.9182667","DOIUrl":null,"url":null,"abstract":"Process mining improves and provides insights for business processes, which are information related to process execution. In general, process mining can be separated into three classes: process discovery, conformance checking and process enhancement. In order to simplify the process model, we make an assumption that both events in the log and tasks in the model have an injective relation in process mining, i.e., do not allow two tasks to share the same label (thus duplicates task). In addition, Duplicate tasks have some issues concerning the quality of process model discovered and the potential indeterminism in conformance checking. In this paper, we perform a systematic literature review of process discovery and conformance checking metrics for duplicate tasks. This review can: (1) provide a comprehensive review of the current work of duplicate tasks in process discovery and conformance checking; (2) help researchers choose proper process mining approach, tools, and metrics; (3) identify research opportunities in duplicate tasks.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAICA50127.2020.9182667","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Process mining improves and provides insights for business processes, which are information related to process execution. In general, process mining can be separated into three classes: process discovery, conformance checking and process enhancement. In order to simplify the process model, we make an assumption that both events in the log and tasks in the model have an injective relation in process mining, i.e., do not allow two tasks to share the same label (thus duplicates task). In addition, Duplicate tasks have some issues concerning the quality of process model discovered and the potential indeterminism in conformance checking. In this paper, we perform a systematic literature review of process discovery and conformance checking metrics for duplicate tasks. This review can: (1) provide a comprehensive review of the current work of duplicate tasks in process discovery and conformance checking; (2) help researchers choose proper process mining approach, tools, and metrics; (3) identify research opportunities in duplicate tasks.