Name
Abstract | ||
|---|---|---|
The most common approach to community identification of directed networks has been to ignore edge directions and apply methods developed for undirected networks. Recently, Leicht and Newman published a work on community identification of directed networks, which is a generalization of the widely used community finding technique of modularity maximization in undirected networks. However, our investigation of this method shows that the method they used does not exploit direction information as they proposed. In this work, we propose an alternative method which exploits the directional information of links properly. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-02469-6_81 | Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering |
Keywords | Field | DocType |
community identification method,directed networks,directional information | Community finding,Exploit,Artificial intelligence,Maximization,Modularity,Machine learning,Mathematics | Conference |
Volume | ISSN | Citations |
5 | 1867-8211 | 3 |
PageRank | References | Authors |
0.39 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Youngdo Kim | 1 | 14 | 1.41 |
| Seung Woo Son | 2 | 296 | 31.43 |
| Hawoong Jeong | 3 | 988 | 190.47 |