Searching for and Ranking Alpha Users in Massive Telecom Social Networks with MapReduce
碩士 === 國立交通大學 === 電信工程研究所 === 101 === In this thesis, we propose novel MapReduce algorithms to search for and rank alpha users in massive telecom social networks. We first apply the principle of divide-and-conquer to find out trusses in a social graph and then use the eigenvector centrality to ident...
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| Format: | Others |
| Language: | en_US |
| Published: |
2013
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| Online Access: | http://ndltd.ncl.edu.tw/handle/11061699860640748477 |
| Summary: | 碩士 === 國立交通大學 === 電信工程研究所 === 101 === In this thesis, we propose novel MapReduce algorithms to search for
and rank alpha users in massive telecom social networks. We first apply
the principle of divide-and-conquer to find out trusses in a social graph and
then use the eigenvector centrality to identify alpha users in the trusses in
parallel. In addition, we propose ranking alpha users in distinct trusses based
on their shortest path coverage. Furthermore, we propose novel algorithms
to efficiently detect and decompose giant components in a social graph. In
addition to synthetic social networks, we have used the proposed algorithms
to analyze real smart phone social networks that are created based on call
detail records collected by a telecom operator.
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