Mining Overlapping Clusters in Networks

Recent advances in social media and social networks have made clustering on very large networks a vibrant and important research topic. In many real world applications, we require clusters to be overlapping [22]. For example, the clusters in a social network are overlapping groups of friends [4], and clusters in scientific collaboration network are overlapping sets of authors sharing some common research interests [2],etc.. Despite a rich literature on overlapping clustering in networks, most the existing works suffer from the following shortcomings.