Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks

Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of complex networks have mainly focused on their network topology. However, in many real world applications, the edges and vertices have associated attributes that are frequently represented as vertex or edge weights. Furthermore, these weights are often not static, instead changing with time and forming a time series. Hence, to fully understand the dynamics of the complex network, we have to consider both network topology and related time series data. In this work, we propose a motif mining approach to identify trend motifs for such purposes. Simply stated, a trend motif describes a recurring subgraph where each of its vertices or edges displays similar dynamics over a userdefined period. Given this, each trend motif occurrence can help reveal significant events in a complex system; frequent trend motifs may...

• Type: Conference
• Year: 2007
• Where: ICDM
• Authors: Ruoming Jin, Scott McCallen, Eivind Almaas
• Keywords: Complex Network, Data Mining, ICDM 2007, Network Topology, Trend Motifs