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Community Detection By Using Cliques: A Survey

المصدر: مجلة الدراسات المستدامة
الناشر: الجمعية العلمية للدراسات التربوية المستدامة
المؤلف الرئيسي: Kadem, baneen Ali (Author)
مؤلفين آخرين: AL-sultany, Ghaidaa (Co-Author)
المجلد/العدد: مج5, ملحق
محكمة: نعم
الدولة: العراق
التاريخ الميلادي: 2023
التاريخ الهجري: 1445
الشهر: أغسطس
الصفحات: 857 - 871
ISSN: 2663-2284
رقم MD: 1399977
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: EduSearch
مواضيع:
كلمات المؤلف المفتاحية:
Social Network | Community Detection | Clique-Based Algorithm | Maximum Clique-Based Algorithm
رابط المحتوى:
صورة الغلاف QR قانون
حفظ في:
المستخلص: One of the most crucial fields that aids in understanding and analyzing the structure of huge and complex networks, such as social networks, collaborative networks, and web graphs, is communities’ detection. The significant elements of research is the extraction of pertinent information from these networks. The goal of community detection is to reduction the application-generated graph into smaller communities with comparable nodes. The counting of cliques in a larger network is a fundamental problem in graph theory. There is many algorithm used for detecting communities and find the cliques, the maximum clique algorithm. In this paper, a detailed survey of various methods applied for finding communities is given first. Then, the technique of clique , maximum clique and maximal clique is discussed and the main works that have been reported to detect social networks communities using these techniques is summarized

ISSN: 2663-2284

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