Effective and Efficient Community Search in Directed Graphs Across Heterogeneous Social Networks

Communities in social networks are useful for many real applications, like product recommendation. This fact has driven the recent research interest in retrieving communities online. Although certain effort has been put into community search, users' information has not been well exploited for effective search. Meanwhile, existing approaches for retrieval of communities are not efficient when applied in huge social networks. Motivated by this, in this paper, we propose a novel approach for retrieving communities online, which makes full use of users' relationship information across heterogeneous social networks. We first investigate an online technique to match pairs of users in different social network and create a new social network, which contains more complete information. Then, we propose k-Dcore, a novel framework of retrieving effective communities in the directed social network. Finally, we construct an index to search communities efficiently for queries. Extensive experiments demonstrate the efficiency and effectivedness of our proposed solution in directed graphs, based on heterogeneous social networks.