… on new trends in deep learning for community detection. Our … progress in deep learning for
community detection. Each … approaches, being deep neural networks, deep graph embedding…

… for understanding the intuition behind community detection, and can be used … community
detection. We provide a thorough theoretical analysis of learning-based community detection …

… To structure this survey, we devised a taxonomy for deep community detection methods
according to the iconic characteristics of the employed deep learning models. The taxonomy …

… to community detection. Taking advantage of the nonlinear representation power of deep
neural … reconstruction (DNR) algorithm for community detection using deep neural networks. …

… Therefore, this paper proposes a highly accurate weighted network method of community
detection based on deep learning. This algorithm first obtains the similarity matrix containing …

… a deep community detection method which includes (1) matrix reconstruction method, (2)
spatial feature extraction method and (3) community detection … a deep community detection …

… The two mainly existing approaches for community detection, … Considering the nonlinear
representation power of deep … a deep neural network architecture for community detection …

… deep learning, it has achieved great success in many applications. This may because deep
… Recently, there are several studies on community detection using deep learning methods, …

… community detection methods we demonstrate improved ability to identify important communities
… Many community detection methods are based on detecting nodes or edges with high …

… challenges of community detection is how to … -communities of) users. With this in mind, this
paper presents a semi-supervised community detection approach, combining deep learning …