{"title":"Effa:用于恢复事件日志的proM插件","authors":"Xiaoxu Xia, Wei Song, Fangfei Chen, Xuansong Li, Pengcheng Zhang","doi":"10.1145/2993717.2993732","DOIUrl":null,"url":null,"abstract":"While event logs generated by business processes play an increasingly significant role in business analysis, the quality of data remains a serious problem. Automatic recovery of dirty event logs is desirable and thus receives more attention. However, existing methods only focus on missing event recovery, or fall short of efficiency. To this end, we present Effa, a ProM plugin, to automatically recover event logs in the light of process specifications. Based on advanced heuristics including process decomposition and trace replaying to search the minimum recovery, Effa achieves a balance between repairing accuracy and efficiency.","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":"17 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2016-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Effa: a proM plugin for recovering event logs\",\"authors\":\"Xiaoxu Xia, Wei Song, Fangfei Chen, Xuansong Li, Pengcheng Zhang\",\"doi\":\"10.1145/2993717.2993732\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While event logs generated by business processes play an increasingly significant role in business analysis, the quality of data remains a serious problem. Automatic recovery of dirty event logs is desirable and thus receives more attention. However, existing methods only focus on missing event recovery, or fall short of efficiency. To this end, we present Effa, a ProM plugin, to automatically recover event logs in the light of process specifications. Based on advanced heuristics including process decomposition and trace replaying to search the minimum recovery, Effa achieves a balance between repairing accuracy and efficiency.\",\"PeriodicalId\":20631,\"journal\":{\"name\":\"Proceedings of the 8th Asia-Pacific Symposium on Internetware\",\"volume\":\"17 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 8th Asia-Pacific Symposium on Internetware\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2993717.2993732\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2993717.2993732","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
While event logs generated by business processes play an increasingly significant role in business analysis, the quality of data remains a serious problem. Automatic recovery of dirty event logs is desirable and thus receives more attention. However, existing methods only focus on missing event recovery, or fall short of efficiency. To this end, we present Effa, a ProM plugin, to automatically recover event logs in the light of process specifications. Based on advanced heuristics including process decomposition and trace replaying to search the minimum recovery, Effa achieves a balance between repairing accuracy and efficiency.