Summarization of Dynamic Graphs

Abstract

In many applications, it is necessary or at least beneficial to explore multiple graphs collectively. These graphs can be temporal instances of the same set of objects (time-evolving graphs), or disparate networks coming from different sources. In this chapter we focus on dynamic networks: Given a large phonecall network over time, how can we describe it to a practitioner with just a few phrases? Other than the traditional assumptions about real-world graphs involving degree skewness, what can we say about their connectivity? For example, is the dynamic graph characterized by many large cliques which appear at fixed intervals of time, or perhaps by several large stars with dominant hubs that persist throughout? In this chapter we focus on these questions, and specifically on constructing concise summaries of large, real-world dynamic graphs in order to better understand their underlying behavior. In this chapter, we extend our work on single-graph summarization which we described in Chapter 2.