Name
Title | ||
|---|---|---|
An event-based framework for characterizing the evolutionary behavior of interaction graphs |
Abstract | ||
|---|---|---|
Interaction graphs are ubiquitous in many elds such as bioinformatics, sociology and physical sciences. There have been many studies in the literature targeted at studying and mining these graphs. However, almost all of them have studied these graphs from a static point of view. The study of the evolution of these graphs over time can provide tremendous insight on the behavior of entities, communities and the o w of information among them. In this work, we present an event-based characterization of critical behavioral patterns for temporally varying interaction graphs. We use non-overlapping snapshots of interaction graphs and develop a framework for capturing and identifying interesting events from them. We use these events to characterize complex behavioral patterns of individuals and communities over time. We show how semantic information can be incorporated to reason about community-behavior events. We also demonstrate the application of behavioral patterns for the purposes of modeling evolution, link prediction and inuence maximization. Finally, we present a diusion model for evolving networks, based on our framework. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1145/1631162.1631164 | ACM Transactions on Knowledge Discovery from Data (TKDD) |
Keywords | Field | DocType |
interaction network,diffusion model | Data mining,Behavioral pattern,Information flow (information theory),Graph,Computer science,Diffusion of innovations,Evolving networks,Artificial intelligence,Snapshot (computer storage),Machine learning,Maximization | Conference |
Volume | Issue | ISSN |
3 | 4 | 1556-4681 |
Citations | PageRank | References |
157 | 7.78 | 26 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sitaram Asur | 1 | 1368 | 64.36 |
| Srinivasan Parthasarathy | 2 | 4666 | 375.76 |
| Duygu Ucar | 3 | 347 | 19.69 |