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Motivated by applications in social network community analysis, we introduce a new clustering paradigm termed motif clustering. Unlike classical clustering, motif clustering aims to minimize the number of clustering errors associated with both edges and certain higher order graph structures (motifs) that represent “atomic units” of social organizations. Our contributions are two-fold: We first introduce...
Recently, social event recommendation, which is to recommend a list of upcoming events to a user, has attracted a lot of research interests. In this paper, we first construct a heterogeneous graph to express the interactions among different types of entities in event-based social network. Based on the constructed graph, we propose a novel recommendation algorithm called reverse random walk with restart...
In this paper, we study the problem of performing multi-label classification on networked data, where each instance in the network is assigned with multiple labels and the connections between instances are driven by various casual reasons. Networked data extracted from social media or web pages may not reflect the relationship between users in real life accurately. By mining the links that actually...
Sina-Microblog, the earliest and biggest microblogging service in China, has become one of the most popular media in information propagation. In order to gain insights into the topological and information diffusing characteristics of microblogging network in China, we crawled Sina-Microblog for about 3 months and obtain the trace of its topology and topics. Compared with other online social networks,...
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