کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
13461581 | 1845223 | 2020 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Modularized convex nonnegative matrix factorization for community detection in signed and unsigned networks
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
فیزیک ریاضی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
NMF-based models in unsigned networks, the links of which are positive links only, have been applied in many aspects, such as community detection, link prediction, etc. However, NMF has been under-explored for community discovery in signed networks due to its constraint of non-negativity. Also, there are few related studies which could find out accurate partitions on both signed and unsigned networks due to their difference of community structure. In this paper, we propose a novel modularized convex nonnegative matrix factorization model which combines signed modularized information with convex NMF model, improving the accuracy of community detection in signed and unsigned networks. As for model selection, we extend the modularity density to signed networks and employ the signed modularity density to determine the number of communities automatically. Finally, the effectiveness of our model is verified on both synthetic and real-world networks.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica A: Statistical Mechanics and its Applications - Volume 539, 1 February 2020, 122904
Journal: Physica A: Statistical Mechanics and its Applications - Volume 539, 1 February 2020, 122904
نویسندگان
Chao Yan, Zhenhai Chang,