G. Naga Chandrika1, Khalid Alnowibet2, K. Sandeep Kautish3, E. Sreenivasa Reddy4, Adel F. Alrasheedi2, Ali Wagdy Mohamed5,6,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5707-5720, 2022, DOI:10.32604/cmc.2022.021186
Abstract Graphs are used in various disciplines such as telecommunication, biological networks, as well as social networks. In large-scale networks, it is challenging to detect the communities by learning the distinct properties of the graph. As deep learning has made contributions in a variety of domains, we try to use deep learning techniques to mine the knowledge from large-scale graph networks. In this paper, we aim to provide a strategy for detecting communities using deep autoencoders and obtain generic neural attention to graphs. The advantages of neural attention are widely seen in the field of NLP… More >
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