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Conference Paper: BetterLife 2.0: large-scale social intelligence reasoning on cloud

TitleBetterLife 2.0: large-scale social intelligence reasoning on cloud
Authors
KeywordsCase base management
CBR
Design considerations
Logical reasoning
Cloud computing
Issue Date2010
PublisherIEEE, Computer Society.
Citation
The 2nd IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2010), Indianapolis, IN., 30 November-3 December 2010. In Proceedings of the 2nd CloudCom, 2010, p. 529-536 How to Cite?
AbstractThis paper presents the design of the BetterLife 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. © 2010 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/152973
ISBN
References

 

DC FieldValueLanguage
dc.contributor.authorHu, Hen_US
dc.contributor.authorWang, Yen_US
dc.contributor.authorWang, CLen_US
dc.date.accessioned2012-07-16T09:53:35Z-
dc.date.available2012-07-16T09:53:35Z-
dc.date.issued2010en_US
dc.identifier.citationThe 2nd IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2010), Indianapolis, IN., 30 November-3 December 2010. In Proceedings of the 2nd CloudCom, 2010, p. 529-536en_US
dc.identifier.isbn978-0-7695-4302-4-
dc.identifier.urihttp://hdl.handle.net/10722/152973-
dc.description.abstractThis paper presents the design of the BetterLife 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. © 2010 IEEE.-
dc.languageengen_US
dc.publisherIEEE, Computer Society.-
dc.relation.ispartofProceedings of the IEEE International Conference on Cloud Computing Technology and Scienceen_US
dc.rightsProceedings of the IEEE International Conference on Cloud Computing Technology and Science. Copyright © IEEE, Computer Society.-
dc.rights©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectCase base management-
dc.subjectCBR-
dc.subjectDesign considerations-
dc.subjectLogical reasoning-
dc.subjectCloud computing-
dc.titleBetterLife 2.0: large-scale social intelligence reasoning on clouden_US
dc.typeConference_Paperen_US
dc.identifier.emailHu, DH: hyhu@cs.hku.hken_US
dc.identifier.emailWang, Y: yfwang@cs.hku.hken_US
dc.identifier.emailWang, CL: clwang@cs.hku.hk-
dc.identifier.authorityWang, CL=rp00183en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/CloudCom.2010.108-
dc.identifier.scopuseid_2-s2.0-79952427411-
dc.identifier.hkuros201880en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79952427411&selection=ref&src=s&origin=recordpage-
dc.identifier.spage529en_US
dc.identifier.epage536en_US
dc.publisher.placeUnited States-
dc.description.otherThe 2nd IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2010), Indianapolis, IN., 30 November-3 December 2010. In Proceedings of the 2nd CloudCom, 2010, p. 529-536-
dc.identifier.scopusauthoridHu, DH=23396949100-
dc.identifier.scopusauthoridWang, Y=36629685900-
dc.identifier.scopusauthoridWang, CL=7501646188-

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