{"title":"BetterLife 2.0: Large-Scale Social Intelligence Reasoning on Cloud","authors":"Dexter H. Hu, Yinfeng Wang, Cho-Li Wang","doi":"10.1109/CloudCom.2010.108","DOIUrl":null,"url":null,"abstract":"This paper presents the design of the Better Life 2.0 framework, which facilitates implementation of large-scale social intelligence application in cloud environment. We argued that more and more mobile social applications in pervasive computing need to be implemented this way, with a lot of user generated activities in social networking websites. We adopted the Case-based Reasoning technique to provide logical reasoning and outlined design considerations when porting a typical CBR framework jCOLIBRI2 to cloud, using Hadoop's various services (HDFS, HBase). These services allow efficient case base management (e.g. case insertion) and distribution of computational intensive jobs to speed up reasoning process more than 5 times. With the scalability merit of MapReduce, we can improve recommendation service with social network analysis that needs to handle millions of users' social activities.","PeriodicalId":130987,"journal":{"name":"2010 IEEE Second International Conference on Cloud Computing Technology and Science","volume":"185 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Second International Conference on Cloud Computing Technology and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CloudCom.2010.108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
This paper presents the design of the Better Life 2.0 framework, which facilitates implementation of large-scale social intelligence application in cloud environment. We argued that more and more mobile social applications in pervasive computing need to be implemented this way, with a lot of user generated activities in social networking websites. We adopted the Case-based Reasoning technique to provide logical reasoning and outlined design considerations when porting a typical CBR framework jCOLIBRI2 to cloud, using Hadoop's various services (HDFS, HBase). These services allow efficient case base management (e.g. case insertion) and distribution of computational intensive jobs to speed up reasoning process more than 5 times. With the scalability merit of MapReduce, we can improve recommendation service with social network analysis that needs to handle millions of users' social activities.