{"title":"Ranking-based business information processing: applications to business solutions and eCommerce systems","authors":"Mao Chen, J. Sairamesh","doi":"10.1109/ICECT.2005.74","DOIUrl":null,"url":null,"abstract":"Extracting crucial information in high volume business data efficiently are critical for enterprises to make timely business decisions and adapt accordingly. This paper proposes a novel ranking-based system that applies knowledge models and utility functions. In a case study for monitoring and analyzing automotive failures in aftermarket services, we shed a light on our ranking mechanism that combines objective business metrics and \"subjective\" domain knowledge. Our experiments using real-world data demonstrate that our methodology is capable of capturing macro view about business performance issues from a small but important fraction of information.","PeriodicalId":312957,"journal":{"name":"Seventh IEEE International Conference on E-Commerce Technology (CEC'05)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seventh IEEE International Conference on E-Commerce Technology (CEC'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECT.2005.74","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
Extracting crucial information in high volume business data efficiently are critical for enterprises to make timely business decisions and adapt accordingly. This paper proposes a novel ranking-based system that applies knowledge models and utility functions. In a case study for monitoring and analyzing automotive failures in aftermarket services, we shed a light on our ranking mechanism that combines objective business metrics and "subjective" domain knowledge. Our experiments using real-world data demonstrate that our methodology is capable of capturing macro view about business performance issues from a small but important fraction of information.