Temporal Social Network: Group Query Processing

With the development of on-line social networks, more and more users and sellers are interested in group analytics which provides insights into common interests with various relationships. This paper addresses this problem from temporal aspect, i.e., temporal group query (TGQ) which gives people the historical view for group forming and changing. To efficiently achieve our goal, we propose two structures to index temporal social network (TSN), and then a simple naive searching method is designed to process the TGQ, after that we argue a more efficient approach can be implemented by update operations instead of iterative graph generations, which we call optimized method. We conduct experiments on real-synthetic dataset, and the results show that our indexes and searching algorithms are capable, and optimized method is much more efficient than the naive one.