Mendeley
TY  _  JOUR
ID  -  1402051943556
TI  -  A Parallel and Efficient Algorithm for Detecting Overlapping Communities in Social Networks
JO  -  Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran
JA  -  ES
LA  -  fa
SN  -  16823745
AU  -  Sabzekar Mostafa
AU  -  Baradaran Nejad Shima
AU  -  Khazaiepoor Mahdi
AU  -  Kherad Mehdi
AD  -  گروه مهندسی کامپیوتر، دانشگاه صنعتی بیرجند
AD  -  گروه مهندسی کامپیوتر، دانشگاه آزاد اسلامی، واحد بیرجند، بیرجند، ایران
AD  -  گروه مهندسی کامپیوتر، دانشگاه آزاد اسلامی، واحد بیرجند، بیرجند، ایران
AD  -  دانشجوی دکتری، گروه مهندسی کامپیوتر، دانشکده فنی و مهندسی - دانشگاه قم - قم - ایران 
Y1  -  2025
PY  -  2025
VL  -  4
IS  -  
SP  -  245
EP  -  258
KW  -  Social networks
KW  -   parallelization
KW  -   community detection
KW  -   overlapping communities.
DO  -  
N2  -  <p style="direction: ltr;">Social networks are not only tools for communication but also represent one of the key potentials in business and commerce. One of the most significant issues in this field is clustering nodes and extracting effective and useful patterns from them, known as community detection. A major challenge in community detection within social networks is the vast number of nodes, which makes any kind of analysis difficult. Another challenge is the overlap of cluster members, referred to as overlapping communities. In such networks, each node may belong to multiple groups. Considering overlaps between communities&mdash;especially in large-scale networks&mdash;poses significant challenges in accurately detecting and identifying communities. Therefore, many studies tend to overlook this issue. In this paper, an approach is proposed to address these challenges. The most time-consuming step in the proposed algorithm, identifying influential nodes, is performed in parallel. Moreover, overlaps between communities are taken into account and analyzed. The results of evaluating the proposed method, in comparison with other existing methods, indicate its superiority in terms of the uniformity of the detected communities.</p>
UR  - rimag.ir/en/Article/43556
L1  - rimag.ir/en/Article/Download/43556
ER  -  
