TY - JOUR
T1 - Improvement of path analysis algorithm in social networks based on HBase
AU - Qiang, Yan
AU - Pei, Bo
AU - Wu, Weili
AU - Zhao, Juanjuan
AU - Zhang, Xiaolong
AU - Li, Yue
AU - Wu, Lidong
N1 - Funding Information:
Acknowledgments This study was supported by the National Natural Science Foundation of China (Grant No. 61202163, 61240035, 61373100); Natural Science Foundation of Shanxi Province (Grant No. 2012011015-1) and Programs for Science and Technology Development of Shanxi Province (Grant No. 20120313032-3). This work was also supported in part by the US National Science Foundation (NSF) under Grant no. CNS-1016320 and CCF-0829993.
PY - 2014/10
Y1 - 2014/10
N2 - When social network has reached hundreds of million users, the analysis of data in social network services becomes very important. Understanding how nodes interconnect in large graphs is an essential problem in many fields. In order to find connecting nodes between two nodes or two groups of source nodes in huge graphs, we propose a parallelized data-mining algorithm to get the shortest path between nodes in a social network based on HBase distributed key/value store. Our algorithm can achieve the shortest path among different nodes in network under the parallel environment. We analyze the social network model by this algorithm first, and then optimize the output from cloud platform by using the intermediary degrees and degree central algorithm. Finally, with a simulated social network, we validate the efficiency of the proposed algorithm. The experiment results indicate that our algorithm can improve the efficiency of parallel breath-first search (BSF).
AB - When social network has reached hundreds of million users, the analysis of data in social network services becomes very important. Understanding how nodes interconnect in large graphs is an essential problem in many fields. In order to find connecting nodes between two nodes or two groups of source nodes in huge graphs, we propose a parallelized data-mining algorithm to get the shortest path between nodes in a social network based on HBase distributed key/value store. Our algorithm can achieve the shortest path among different nodes in network under the parallel environment. We analyze the social network model by this algorithm first, and then optimize the output from cloud platform by using the intermediary degrees and degree central algorithm. Finally, with a simulated social network, we validate the efficiency of the proposed algorithm. The experiment results indicate that our algorithm can improve the efficiency of parallel breath-first search (BSF).
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U2 - 10.1007/s10878-013-9675-z
DO - 10.1007/s10878-013-9675-z
M3 - Article
AN - SCOPUS:84906948419
SN - 1382-6905
VL - 28
SP - 588
EP - 599
JO - Journal of Combinatorial Optimization
JF - Journal of Combinatorial Optimization
IS - 3
ER -