{"title":"支持分布式实时分析的基于事件的模型:财务案例研究","authors":"Z. Milosevic, A. Berry, Weisi Chen, F. Rabhi","doi":"10.1109/EDOC.2015.26","DOIUrl":null,"url":null,"abstract":"This paper describes key modelling concepts for events, event patterns and related concepts needed to develop a distributed software framework for real-time business analytics. These concepts are specified by means of a minimal meta-model, whose implementation can enable better interoperability between different event processing systems. This in turn can support better, distributed, collaborative analytics applications in many domains. We show an implementation of our solution approach using a case study of several business analytics problems in finance.","PeriodicalId":112281,"journal":{"name":"2015 IEEE 19th International Enterprise Distributed Object Computing Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An Event-Based Model to Support Distributed Real-Time Analytics: Finance Case Study\",\"authors\":\"Z. Milosevic, A. Berry, Weisi Chen, F. Rabhi\",\"doi\":\"10.1109/EDOC.2015.26\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes key modelling concepts for events, event patterns and related concepts needed to develop a distributed software framework for real-time business analytics. These concepts are specified by means of a minimal meta-model, whose implementation can enable better interoperability between different event processing systems. This in turn can support better, distributed, collaborative analytics applications in many domains. We show an implementation of our solution approach using a case study of several business analytics problems in finance.\",\"PeriodicalId\":112281,\"journal\":{\"name\":\"2015 IEEE 19th International Enterprise Distributed Object Computing Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 19th International Enterprise Distributed Object Computing Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EDOC.2015.26\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 19th International Enterprise Distributed Object Computing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDOC.2015.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Event-Based Model to Support Distributed Real-Time Analytics: Finance Case Study
This paper describes key modelling concepts for events, event patterns and related concepts needed to develop a distributed software framework for real-time business analytics. These concepts are specified by means of a minimal meta-model, whose implementation can enable better interoperability between different event processing systems. This in turn can support better, distributed, collaborative analytics applications in many domains. We show an implementation of our solution approach using a case study of several business analytics problems in finance.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
