BetterLife 2.0: Large-Scale Social Intelligence Reasoning on Cloud

Dexter H. Hu, Yinfeng Wang, Cho-Li Wang
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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.
美好生活2.0:云上大规模社会智能推理
本文提出了美好生活2.0框架的设计,便于在云环境下实现大规模的社会智能应用。我们认为,越来越多的普适计算中的移动社交应用程序需要以这种方式实现,在社交网站中有大量用户生成的活动。在使用Hadoop的各种服务(HDFS, HBase)将典型的CBR框架jCOLIBRI2移植到云端时,我们采用了基于案例的推理技术来提供逻辑推理和概述设计注意事项。这些服务允许有效的案例库管理(例如案例插入)和计算密集型工作的分配,从而将推理过程加快5倍以上。利用MapReduce的可扩展性优点,我们可以利用需要处理数百万用户社交活动的社交网络分析来改进推荐服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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