Selecting Key Person of Social Network Using Skyline Query in MapReduce Framework
Selecting Key Person of Social Network Using Skyline Query in MapReduce Framework
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DOI：
10.1109/candar.2015.84
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发表时间：
2015-12
期刊：
影响因子：
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通讯作者：
Asif Zaman;M. A. Siddique;Annisa;Y. Morimoto
中科院分区：
文献类型：
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作者：
Asif Zaman;M. A. Siddique;Annisa;Y. Morimoto
研究了从社交网络中选择少数重要人物的问题。我们应用天际线查询来选取社会网络的关键人物。Skyline查询从社交网络中选择不受另一个人支配的人。与一般的skyline查询不同，从社交网络中选择关键人物更加复杂，因为我们需要考虑社交网络的不同度量。此外，社交网络是海量数据的容器，并且每小时都在以巨大的数量增加。它是致力于基于社区的输入，互动，内容共享和协作的在线通信渠道的集合。我们使用MapReduce框架来加速计算和并行性。大量的实验表明，对社会活动、社会关系和社会共享内容的分析有助于找到关键人物。
This paper considers a problem of selecting small number of important person from social networks. We applied skyline query for selecting the key person of social network. Skyline query selects persons from social network those are not dominated by another person. Different from general skyline query, selecting key person from social networks is more complicated because we need to consider different metrics of social network. In addition, social networks is a container of massive data and each and every hour it is increasing in gigantic amount. It is the collective of online communications channels dedicated to community-based input, interaction, content-sharing, and collaboration. We use MapReduce framework to speed up the computation and parallelism. An extensive set of experiments shows that the analysis of social activities, social relationships, and socially shared contents helps to find key person.