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Network Nodes Community Detection Based on Deep Learning

Credit to Download: 1 | Page Numbers 6 | Abstract Views: 133
Year: 2018
Present: پوستري
COI code: IRANWEB04_005
Paper Language: English

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Authors Network Nodes Community Detection Based on Deep Learning

  Mohammad Mehdi Keikha - PhD Candidate, University of Tehran, Tehran, Iran Faculty member, University of Sistan and Baluchestan, Zahedan, Iran
  Maseud Rahgozar - Associate Professor, University of Tehran, Tehran


Network clustering is one of the problems that has attracted many researchers in recent years. In this issue, each user is associated with a specific community based on the various features of the network, including the structure. In the recent years, deep learning is widely used to extract the feature vector of nodes then the vectors are used to find the community of each node. In this paper, a network representation learning algorithm is presented based on the information of the neighbors of each node and communities on the network. The results show that our nodes’ representation method offers a better quality clustering of social networking users than the previous network representation learning methods.


Network Clustering, Deep Learning, Node Representation Vector, Network Communities

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COI code: IRANWEB04_005

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Keikha, Mohammad Mehdi & Maseud Rahgozar, 2018, Network Nodes Community Detection Based on Deep Learning, 4th International Conference on Web Research, تهران, دانشگاه علم و فرهنگ, the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
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The University/Research Center Information:
Type: state university
Paper No.: 54106
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