Andreas Bögl, Christine Natschläger, M. Karlinger, M. Schrefl
{"title":"Exploiting Process Patterns and Process Instances to Support Adaptability of Dynamic Business Processes","authors":"Andreas Bögl, Christine Natschläger, M. Karlinger, M. Schrefl","doi":"10.1109/DEXA.2014.46","DOIUrl":null,"url":null,"abstract":"The traditional approach for business process modeling is rather static, since all possible process flows must be specified at design-time. This restricts the possibility of the user to react to unexpected situations, so conventional business processes cannot represent the flexible way in which human actors would handle discrepancies between real-world and computerized activities. This paper presents a new approach for dynamic business processes that automatically adapts to changed circumstances based on domain-specific process patterns and an evaluation of related process instances. The presented approach not only finds potential alternatives for failed activities, it also ranks them by exploiting process knowledge implicitly captured by former business process execution.","PeriodicalId":291899,"journal":{"name":"2014 25th International Workshop on Database and Expert Systems Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 25th International Workshop on Database and Expert Systems Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEXA.2014.46","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The traditional approach for business process modeling is rather static, since all possible process flows must be specified at design-time. This restricts the possibility of the user to react to unexpected situations, so conventional business processes cannot represent the flexible way in which human actors would handle discrepancies between real-world and computerized activities. This paper presents a new approach for dynamic business processes that automatically adapts to changed circumstances based on domain-specific process patterns and an evaluation of related process instances. The presented approach not only finds potential alternatives for failed activities, it also ranks them by exploiting process knowledge implicitly captured by former business process execution.