کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7376094 1480077 2018 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A fast community detection method in bipartite networks by distance dynamics
ترجمه فارسی عنوان
روش سریع تشخیص جامعه در شبکه های دو طرفه با پویایی فاصله
کلمات کلیدی
شباهت گره، تشخیص جامعه، شبکه های دو طرفه بزرگ،
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات فیزیک ریاضی
چکیده انگلیسی
Many real bipartite networks are found to be divided into two-mode communities. In this paper, we formulate a new two-mode community detection algorithm BiAttractor. It is based on distance dynamics model Attractor proposed by Shao et al. with extension from unipartite to bipartite networks. Since Jaccard coefficient of distance dynamics model is incapable to measure distances of different types of vertices in bipartite networks, our main contribution is to extend distance dynamics model from unipartite to bipartite networks using a novel measure Local Jaccard Distance (LJD). Furthermore, distances between different types of vertices are not affected by common neighbors in the original method. This new idea makes clear assumptions and yields interpretable results in linear time complexity O(|E|) in sparse networks, where |E| is the number of edges. Experiments on synthetic networks demonstrate it is capable to overcome resolution limit compared with existing other methods. Further research on real networks shows that this model can accurately detect interpretable community structures in a short time.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica A: Statistical Mechanics and its Applications - Volume 496, 15 April 2018, Pages 108-120
نویسندگان
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