کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4961808 1446519 2016 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Community Detection by Consensus Genetic-based Algorithm for Directed Networks
ترجمه فارسی عنوان
تشخیص جامعه با استفاده از الگوریتم مبتنی بر ژنتیک برای شبکه های مستقیم
کلمات کلیدی
الگوریتم های ژنتیک، خوشه بندی اجماع، مدولار، شبکه های هدایت شده
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی

Finding communities in networks is a commonly used form of network analysis. There is a myriad of community detection algorithms in the literature to perform this task. In spite of that, the number of community detection algorithms in directed networks is much lower than in undirected networks. However, evaluation measures to estimate the quality of communities in undirected networks nowadays have its adaptation to directed networks as, for example, the well-known modularity measure. This paper introduces a genetic-based consensus clustering to detect communities in directed networks with the directed modularity as the fitness function. Consensus strategies involve combining computational models to improve the quality of solutions generated by a single model. The reason behind the development of a consensus strategy relies on the fact that recent studies indicate that the modularity may fail in detecting expected clusterings. Computational experiments with artificial LFR networks show that the proposed method was very competitive in comparison to existing strategies in the literature.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Computer Science - Volume 96, 2016, Pages 90-99
نویسندگان
, , ,