{"title":"过程挖掘:块发现的矩阵表示","authors":"Boushaba Souhail, M. Kabbaj, Z. Bakkoury","doi":"10.1109/SITA.2013.6560816","DOIUrl":null,"url":null,"abstract":"Modeling is practically time-consuming and error-prone task. To help making process modeling easier, the use of process discovery is considered to be an efficient way to create a fitting process model. In this paper, we propose a new method for process discovery based on a process matrix representation to reduce the complexity of discovered processes.","PeriodicalId":145244,"journal":{"name":"2013 8th International Conference on Intelligent Systems: Theories and Applications (SITA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Process mining: Matrix representation for bloc discovery\",\"authors\":\"Boushaba Souhail, M. Kabbaj, Z. Bakkoury\",\"doi\":\"10.1109/SITA.2013.6560816\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Modeling is practically time-consuming and error-prone task. To help making process modeling easier, the use of process discovery is considered to be an efficient way to create a fitting process model. In this paper, we propose a new method for process discovery based on a process matrix representation to reduce the complexity of discovered processes.\",\"PeriodicalId\":145244,\"journal\":{\"name\":\"2013 8th International Conference on Intelligent Systems: Theories and Applications (SITA)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 8th International Conference on Intelligent Systems: Theories and Applications (SITA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SITA.2013.6560816\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th International Conference on Intelligent Systems: Theories and Applications (SITA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITA.2013.6560816","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Process mining: Matrix representation for bloc discovery
Modeling is practically time-consuming and error-prone task. To help making process modeling easier, the use of process discovery is considered to be an efficient way to create a fitting process model. In this paper, we propose a new method for process discovery based on a process matrix representation to reduce the complexity of discovered processes.