آمار
| تعداد نشریات | 36 |
| تعداد شماره‌ها | 1,208 |
| تعداد مقالات | 8,740 |
| تعداد مشاهده مقاله | 7,270,507 |
| تعداد دریافت فایل اصل مقاله | 4,252,963 |
روش توزیعی تشخیص انجمن در شبکههای اجتماعی بزرگ بر اساس انتشار برچسب | ||
| پدافند الکترونیکی و سایبری | ||
| مقاله 1، دوره 8، شماره 4 - شماره پیاپی 32، دی 1399، صفحه 1-15 اصل مقاله (1.19 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| نویسندگان | ||
| محمد حسینی1؛ امین اله مه آبادی* 2 | ||
| 1کارشناسی ارشد، گروه مهندسی کامپیوتر، دانشگاه شاهد | ||
| 2هیات علمی دانشکده فنی مهندسی دانشگاه شاهد | ||
| تاریخ دریافت: 05 اردیبهشت 1400، تاریخ پذیرش: 05 اردیبهشت 1400 | ||
| چکیده | ||
| تشخیص انجمنهای همپوشان در شبکههای اجتماعی بسیار بزرگ با عاملهای هوشمند یک مساله سخت و مهم است که قدرت تشخیص و تحلیل آن شبکهها را از حالت بیدرنگِ برخط خارج میکند. همپوشانی انجمنها در کنار افزایش ابعاد و ارتباطات این شبکهها به چالشهای پیچیدگی زمان زیاد جستجوی انجمنها و افزایش طاقتفرسای حافظه مصرفی منجر میشود که از قابلیت کنترل سریع آن‌ها میکاهد. ارائه روشهای توزیعی مقیاسپذیر تصادفی و عاملگرا، بر اساس انتشار برچسب در شبکههای بسیار بزرگ و پیچیده به کاهش زمان جستجو و تسریع تشخیص کمک میکند. این مقاله روش توزیعی نوین مقیاسپذیر عاملگرا برای تشخیص انجمنهای همپوشان بر اساس انتشار برچسب توانسته با محدودسازی انتشار پیام و استفاده از معیارهای جدید بر روی معماری چندهسته‌ای، به پیچیدگی خطی زمان اجرا و حافظه مصرفی دست یابد. روش پیشنهادی با آزمون بر روی مجموعه داده‌های بسیار بزرگ شبکههای اجتماعی، از نظر زمان اجرا در شبکههای بزرگ تا 9 برابر تسریع و از نظر پیمانه‌ای از %3 تا %100 بهبود دارد و در یافتن انجمنهای همپوشان بسیار دقیق و سریع عمل میکند. | ||
| کلیدواژه‌ها | ||
| شبکه های اجتماعی؛ پردازش توزیعی؛ تشخیص انجمن های همپوشان؛ الگوریتم انتشار برچسب | ||
| عنوان مقاله [English] | ||
| A Distributed Approach to Community Detection in Large Social Networks Based on Label Propagation | ||
| نویسندگان [English] | ||
| M. Huseini1؛ Aminollah Mahabadi2 | ||
| 1shahed university | ||
| 2Computer Engineering Department, Shahed University, Tehran, Iran. Acoustic Research Center , Shahed University, Tehran, Iran. | ||
| چکیده [English] | ||
| Detection of overlapping communities in large complex social networks with intelligent agents, is an NP problem with great time complexity and large memory usage and no simultaneous online solution. Proposing a novel distributed label propagation approach can help to decrease the searching time and reduce the memory space usage. This paper presents a scalable distributed overlapping community detection approach based on the label propagation method by proposing a novel algorithm and three new metrics to expand scalability and improve modularity through agent-based implementation and good memory allocation in a multi-core architecture. The experimental results of large real datasets over the state-of-the-art SLPA approach show that the execution time speeds up by 900% and the modularity improves by 3% to 100% thus producing fast and accurate detection of overlapped communities. | ||
| کلیدواژه‌ها [English] | ||
| Social Networks, Distributed Processing, Overlapping Community Detection, Label Propagation Algorithm | ||
| مراجع | ||
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