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Cycloreversion-enhanced toughness and degradability in mechanophore-embedded end-linked polymer networks. [PDF]
Nat CommunLi Z, Tang S.
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Network Embedding for Community Detection in Attributed Networks
ACM Transactions on Knowledge Discovery From Data, 2020Community detection aims to partition network nodes into a set of clusters, such that nodes are more densely connected to each other within the same cluster than other clusters. For attributed networks, apart from the denseness requirement of topology structure, the attributes of nodes in the same community should also be homogeneous ...
Jianbin Huang +2 more
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Relation constrained attributed network embedding
Information Sciences, 2020Abstract Network embedding aims at learning a low-dimensional dense vector for each node in the network. In recent years, it has attracted great research attention due to its wide applications. Most existing studies model the graph structure only and neglect the attribute information.
Tieyun Qian
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Community-oriented attributed network embedding
Knowledge-Based Systems, 2020Abstract Network embedding aims to map vertices in a complex network into a continuous low-dimensional vector space. Meanwhile, the original network structure and inherent properties must be preserved. Most of the existing methods merely focus on preserving local structural features of vertices, whereas they largely ignore the community patterns and ...
Yuan Gao, Maoguo Gong, Yu Xie
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Deep Attributed Network Embedding by Preserving Structure and Attribute Information
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021Network embedding aims to learn distributed vector representations of nodes in a network. The problem of network embedding is fundamentally important. It plays crucial roles in many applications, such as node classification, link prediction, and so on. As the real-world networks are often sparse with few observed links, many recent works have utilized ...
Richang Hong, Le Wu, Yong Ge
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Attribute Network Alignment Based on Network Embedding
2021 7th International Conference on Computing and Data Engineering, 2021Nodes with similar network structure and attribute features probably distribute across different networks. For instance, people tend to have accounts across various social networks. In recent years, network alignment to identify potential correspondences between nodes across networks has been research focus on social computing.
Fan Yang, Wenxin Liang, Linlin Zong
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Attributed Network Embedding with Community Preservation
2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), 2020Network embedding (NE) is a method that maps nodes in a network into a low-dimensional and continuous vector space while maintains inherent features of the network. Most existing algorithms for NE focus on one or two of the aspects of topological structure, node attributes or community structure information, but without integrating the three in a ...
Huang, T +4 more
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Attributed Signed Network Embedding
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017The major task of network embedding is to learn low-dimensional vector representations of social-network nodes. It facilitates many analytical tasks such as link prediction and node clustering and thus has attracted increasing attention. The majority of existing embedding algorithms are designed for unsigned social networks.
Suhang Wang +3 more
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