{"title":"Interactive Poster: Visual Mining of Business Process Data","authors":"M. Hao, D. Keim, U. Dayal, Jörn Schneidewind","doi":"10.1109/INFVIS.2004.41","DOIUrl":null,"url":null,"abstract":"Business process data is inherently large and complex, most often too complex to be directly visualized. Usually the business operations consist of many steps and alternatives and every data instance may take a different path through the process. In Figure 1, we show a fraud analysis process schema. Note that this business process is a very simple one; realistic business processes are at least 10 times larger.","PeriodicalId":109217,"journal":{"name":"IEEE Symposium on Information Visualization","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Symposium on Information Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFVIS.2004.41","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Business process data is inherently large and complex, most often too complex to be directly visualized. Usually the business operations consist of many steps and alternatives and every data instance may take a different path through the process. In Figure 1, we show a fraud analysis process schema. Note that this business process is a very simple one; realistic business processes are at least 10 times larger.