Welcome to the InfoSci Platform
Graph Mining Techniques: Focusing on Discriminating between Real and Synthetic Graphs

Graph Mining Techniques: Focusing on Discriminating between Real and Synthetic Graphs

Ana Paula Appel, Christos Faloutsos, Caetano Traina Junior
Copyright: © 2012 |Pages: 21
ISBN13: 9781613500538|ISBN10: 161350053X|EISBN13: 9781613500545
DOI: 10.4018/978-1-61350-053-8.ch010
Cite Chapter Cite Chapter

MLA

Appel, Ana Paula, et al. "Graph Mining Techniques: Focusing on Discriminating between Real and Synthetic Graphs." Graph Data Management: Techniques and Applications, edited by Sherif Sakr and Eric Pardede, IGI Global, 2012, pp. 239-259. https://doi.org/10.4018/978-1-61350-053-8.ch010

APA

Appel, A. P., Faloutsos, C., & Junior, C. T. (2012). Graph Mining Techniques: Focusing on Discriminating between Real and Synthetic Graphs. In S. Sakr & E. Pardede (Eds.), Graph Data Management: Techniques and Applications (pp. 239-259). IGI Global. https://doi.org/10.4018/978-1-61350-053-8.ch010

Chicago

Appel, Ana Paula, Christos Faloutsos, and Caetano Traina Junior. "Graph Mining Techniques: Focusing on Discriminating between Real and Synthetic Graphs." In Graph Data Management: Techniques and Applications, edited by Sherif Sakr and Eric Pardede, 239-259. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-61350-053-8.ch010

Export Reference

Mendeley
Favorite

Abstract

Graphs appear in several settings, like social networks, recommendation systems, computer communication networks, gene/protein biological networks, among others. A large amount of graph patterns, as well as graph generator models that mimic such patterns have been proposed over the last years. However, a deep and recurring question still remains: “What is a good pattern?” The answer is related to finding a pattern or a tool able to help distinguishing between actual real-world and fake graphs. Here we explore the ability of ShatterPlots, a simple and powerful algorithm to tease out patterns of real graphs, helping us to spot fake/masked graphs. The idea is to force a graph to reach a critical (“Shattering”) point, randomly deleting edges, and study its properties at that point.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.