Results 11 to 20 of about 3,653 (212)
Time-Weighted Community Search Based on Interest
Applied Sciences, 2022 Community search aims to provide users with personalized community query services. It is a prerequisite for various recommendation systems and has received widespread attention from academia and industry.
Jing Liu, Yong Zhong
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Detecting Anomalies in Network Communities Based on Structural and Attribute Deviation
Applied Sciences, 2022 Anomaly detection in online social networks (OSNs) is an important data mining task that aims to detect unexpected and suspicious users. To enhance anomaly exploration, anomaly ranking is used to assess the degree of user anomaly rather than applying ...
Hedia Zardi +3 more
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Attributed Social Network Embedding [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2018 12 pages, 7 ...
Lizi Liao +3 more
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Network Embedding Algorithm Taking in Variational Graph AutoEncoder
Mathematics, 2022 Complex networks with node attribute information are employed to represent complex relationships between objects. Research of attributed network embedding fuses the topology and the node attribute information of the attributed network in the common ...
Dongming Chen +4 more
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Attributed Network Representation Learning Based on Matrix Factorization [PDF]
Jisuanji gongcheng, 2020 To combine the information of network topological structure and node attribute to improve the quality of network representation learning,this paper proposes a new attributed network representation learning algorithm,named ANEMF.The algorithm introduces ...
ZHANG Pan, LU Guangyue, Lü Shaoqing, ZHAO Xueli
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Method of Attributed Heterogeneous Network Embedding with Multiple Features [PDF]
Jisuanji kexue, 2022 Network embedding aims to represent nodes in unstructured network with low-dimensional,real-valued vectors,so that node embedding can retain the structural and attribute features of the original network as much as possible.However,current research mainly
TANG Qi-you, ZHANG Feng-li, WANG Rui-jin, WANG Xue-ting, ZHOU Zhi-yuan, HAN Ying-jun
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Binarized attributed network embedding [PDF]
2018 IEEE International Conference on Data Mining (ICDM), 2018 Attributed network embedding enables joint representation learning of node links and attributes. Existing attributed network embedding models are designed in continuous Euclidean spaces which often introduce data redundancy and impose challenges to storage and computation costs.
Hong Yang 0003 +5 more
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Co-Embedding Attributed Networks [PDF]
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019 Existing embedding methods for attributed networks aim at learning low-dimensional vector representations for nodes only but not for both nodes and attributes, resulting in the fact that they cannot capture the affinities between nodes and attributes. However, capturing such affinities is of great importance to the success of many real-world attributed
Zaiqiao Meng +3 more
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Attributed Network Embedding Based on Matrix Factorization and Community Detection [PDF]
Jisuanji kexue, 2021 An attributed network contains not only the complex topological structure but also the nodes with rich attribute information.It can be used to more effectively model modern information systems than traditional networks.Community detection of the ...
XU Xin-li, XIAO Yun-yue, LONG Hai-xia, YANG Xu-hua, MAO Jian-fei
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Community detection in Attributed Network [PDF]
Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, 2018 Graph clustering techniques are very useful for detecting densely connected groups in large graphs. Many existing graph clustering methods mainly focus on the topological structure, but ignore the vertex properties. Existing graph clustering methods have been recently extended to deal with nodes attribute. First we motivate the interest in the study of
Issam Falih +3 more
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