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A Novel Method for Detection and Analysis in a Network of Overlap Able Communities

المصدر: مجلة الدراسات المستدامة
الناشر: الجمعية العلمية للدراسات التربوية المستدامة
المؤلف الرئيسي: Tuma, Bashar Mohammed (Author)
مؤلفين آخرين: Abdulsahib, Laith Ali (Co-Author)
المجلد/العدد: مج5, ملحق
محكمة: نعم
الدولة: العراق
التاريخ الميلادي: 2023
التاريخ الهجري: 1445
الشهر: أغسطس
الصفحات: 1921 - 1932
ISSN: 2663-2284
رقم MD: 1399793
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: EduSearch
مواضيع:
كلمات المؤلف المفتاحية:
Overlapping Community Detection | Seed Algorithm | Facebook | Data Learning | Network Metric
رابط المحتوى:
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041 |a eng 
044 |b العراق 
100 |9 740118  |a Tuma, Bashar Mohammed  |e Author 
245 |a A Novel Method for Detection and Analysis in a Network of Overlap Able Communities 
260 |b الجمعية العلمية للدراسات التربوية المستدامة  |c 2023  |g أغسطس  |m 1445 
300 |a 1921 - 1932 
336 |a بحوث ومقالات  |b Article 
520 |b In the domain of Network Data Processing and Data Learning, the identification of communities is crucial for comprehending the functional characteristics of networks. Overlapping community detection, which involves clusters with shared nodes, has become increasingly important in the context of real-world networks. However, there is still a requirement for additional research and the creation of innovative algorithms that consider various factors. This research proposes an updated method for perceiving the inferences within network communities. It introduces a multi-stage approach that starts by identifying seed nodes and concludes by discovering overlapping communities. The novelty lies in the use of a graph/network metric to identify significant seed nodes. The research focuses on two categories: identifying highly significant nodes based on similarity measures and recognizing cluster centers that maximize community density. The experimental outcomes validate the efficiency and scalability of the proposed methodology in identifying overlapping communities in large-scale real-world networks. Through a comparative analysis against state-of-the-art methods, the performance of the proposed approach is further confirmed. This study makes a significant contribution to the field of community detection by presenting an innovative approach that takes into account overlapping communities and integrates graph/network metrics. The results offer valuable insights into the characteristics and functional properties of networks, thereby facilitating advancements in network data processing and data learning methodologies. 
653 |a المجتمعات المتداخلة  |a علوم الحاسب  |a خصائص الشبكات  |a منهجيات التعلم 
692 |b Overlapping Community Detection  |b Seed Algorithm  |b Facebook  |b Data Learning  |b Network Metric 
700 |9 740120  |a Abdulsahib, Laith Ali  |e Co-Author 
773 |4 التربية والتعليم  |6 Education & Educational Research  |c 082  |e Journal of Sustainable Studies  |f Mağallaẗ al-dirāsāt al-mustadāmaẗ  |l 988  |m مج5, ملحق  |o 2053  |s مجلة الدراسات المستدامة  |v 005  |x 2663-2284 
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995 |a EduSearch 
999 |c 1399793  |d 1399793 

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