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Betweenness centrality is a fundamental centrality measure that quantifies how important a node or an edge is, within a network, based on how often it lies on the shortest paths between all pairs of nodes. In this paper, we develop a scalable distributed algorithm, which enables every node in a network to estimate its own betweenness and the betweenness of edges incident on it with only local interaction...
Collaborative recommender systems use various types of information to help customers find products of personalized interest. To increase the usefulness of collaborative recommender systems in certain circumstances, it could be desirable to merge recommender system databases between companies, thus expanding the data pool. This can lead to privacy disclosure hazards during the merging process. This...
Privacy is ultimately important, and there is a fair amount of research about it. However, few empirical studies about the cost of privacy are conducted. In the area of secure multiparty computation, the scalar product has long been reckoned as one of the most promising building blocks in place of the classic logic gates. The reason is not only the scalar product complete, which is as good as logic...
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