A query based approach for mining evolving graphs

Abstract

An evolving graph is a graph that can change over time. Such graphs can be applied in modelling a wide range of real-world phenomena, like computer networks, social networks and protein interaction networks. This paper addresses the novel problem of querying evolving graphs using spatio-temporal patterns. In particular, we focus on answering selection queries, which can discover evolving subgraphs that satisfy both a temporal and a spatial predicate. We investigate the efficient implementation of such queries and experimentally evaluate our techniques using real-world evolving graph datasets - Internet connectivity logs and the Enron email corpus. We show that is possible to use queries to d..