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Community discovery is a leading research topic in social network analysis. In this paper, we present an ego-network probabilistic graphical model (ENPGM) which encodes users’ feature similarities and the causal dependencies between users’ profiles, communities, and ego networks. The model comprises three parts: a profile similarity probabilistic graph, social circle vector, and relationship probabilistic...
In data-mining algorithms contingency tables are frequently built from ADtrees, as ADtrees have been demonstrated to be an efficient data structure for caching sufficient statistics. This paper introduces three modifications. The first two use a one-dimensional array and a hash map for representing contingency tables, and the third uses the non-recursive approach to build contingency tables from sparse...
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