山东科学2013，Vol.26Issue(2)：92-97,6.DOI:10.3976/j.issn.1002-4026.2013.02.018
基于概率与推断的社交网络聚类技术研究
Probability and interference based social network clustering technology
摘要
Abstract
We apply Locality Sensitive Hashing (LSH) to graph clustering, and then present a new clustering technology, Probabilistic Graph Cluster (PGC). We also compare the similarity of the neighbor set of every node in a graph, and verify it with Bayesian statistic inference to find the most compact and inexact clustering in linear time. Experimental results show that PGC is more scalable with the enlargement of a graph and that the clustering speed of PGC is twice faster than that of PageRank Cluster in real data sets, PGC is therefore an effective and alternative solution.关键词
图/聚类/概率/位置敏感哈希算法Key words
graph/clustering/probability/LSH分类
信息技术与安全科学引用本文复制引用
宋传超,王庚..基于概率与推断的社交网络聚类技术研究[J].山东科学,2013,26(2):92-97,6.
