Online social network services have become indispensable in people's daily life. The analysis of data in social network services often involves data mining techniques. However, the quick increase of users in such services posts challenges to develop effective data mining algorithms to deal with large social network data. In this paper, we propose a data-mining algorithm to get the shortest path between nodes in a social network. Based on HBase[1], this algorithm analyzes the social network model, and uses the intermediary degrees and degree central algorithm to optimize the output from cloud platform. With a simulated social network, we validate the efficiency of the algorithm. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Qiang, Y., Lu, J., Wu, W., Zhao, J., Zhang, X., Li, Y., & Wu, L. (2013). Social network path analysis based on HBase. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7936 LNCS, pp. 770–779). https://doi.org/10.1007/978-3-642-38768-5_70
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