کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
393223 | 665579 | 2013 | 11 صفحه PDF | دانلود رایگان |
The detection of network communities has attracted significant research attention lately. To discover such structures, a mathematical measure known as modularity is often used for optimization. Unfortunately, the optimization is NP-hard, and approximated solutions have to be sought for large networks. In this paper, we propose a nonlinear programming method for optimization that is based on the augmented Lagrangian technique. We further identify the inherent connection between the proposed method and positive semi-definite programming and its low-rank reduction, which helps to justify the performance of the method. Compared with previously published approaches, the proposed method is empirically efficient and effective at detecting underlying network communities.
Journal: Information Sciences - Volume 229, 20 April 2013, Pages 18–28