Survey of Algorithms based on Dynamic Graph Mining
Neelu Chaudhary, Hardeo Kumar Thakur · 2018
Now a days people find social networks as an effective means of communication and interaction. Therefore, it is beneficial to analyse the information from these social networks to get the idea of dynamics of human interaction. The basic aspect to understand in behavioral analysis of human interactions is to extract the idea of how and when the communication takes place or unfold. Graph mining is the efficient way to analyse such data and get the required information. As the nature of data involved is dynamic in nature i.e changes wrt time, therefore to mine this type of dynamic data is a topic of interest these days in the form of dynamic graph mining, where time considerations are explicitly incorporated in a set of graph. Dynamic graph is a set of consecutive timestep graphs which can be analysed based on different patterns like frequent, periodic, trend motif, clique etc. In this paper we represent overview of different algorithm used to mine and analyse the evolving patterns in dynamic graph.