Results 51 to 60 of about 8,419,643 (305)
Who Are the Phishers? Phishing Scam Detection on Ethereum via Network Embedding [PDF]
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019 Recently, blockchain technology has become a topic in the spotlight but also a hotbed of various cybercrimes. Among them, phishing scams on blockchain have been found to make a notable amount of money, thus emerging as a serious threat to the trading ...
Jiajing Wu +6 more
semanticscholar +1 more source
Multi-Source and Multi-modal Deep Network Embedding for Cross-Network Node Classification
ACM Transactions on Knowledge Discovery from DataIn recent years, to address the issue of networked data sparsity in node classification tasks, cross-network node classification (CNNC) leverages the richer information from a source network to enhance the performance of node classification in the target
Hongwei Yang +4 more
semanticscholar +1 more source
Embedding of Virtual Network Requests over Static Wireless Multihop Networks
, 2012 Network virtualization is a technology of running multiple heterogeneous network architecture on a shared substrate network. One of the crucial components in network virtualization is virtual network embedding, which provides a way to allocate physical ...
Ok, Jungseul +4 more
core +1 more source
Semisupervised Community Preserving Network Embedding with Pairwise Constraints
Complexity, 2020 Network embedding aims to learn the low-dimensional representations of nodes in networks. It preserves the structure and internal attributes of the networks while representing nodes as low-dimensional dense real-valued vectors.
Dong Liu +4 more
doaj +1 more source
Susceptible-infected-spreading-based network embedding in static and temporal networks
EPJ Data Science, 2020 Link prediction can be used to extract missing information, identify spurious interactions as well as forecast network evolution. Network embedding is a methodology to assign coordinates to nodes in a low-dimensional vector space. By embedding nodes into
Xiu-Xiu Zhan +4 more
doaj +1 more source
Structural Deep Embedding for Hyper-Networks
, 2018 Network embedding has recently attracted lots of attentions in data mining. Existing network embedding methods mainly focus on networks with pairwise relationships. In real world, however, the relationships among data points could go beyond pairwise, i.e.
Cui, Peng +4 more
core +1 more source
Discrete Network Embedding [PDF]
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Network embedding aims to seek low-dimensional vector representations for network nodes, by preserving the network structure. The network embedding is typically represented in continuous vector, which imposes formidable challenges in storage and computation costs, particularly in large-scale applications.
Xiaobo Shen +4 more
openaire +1 more source
Unsupervised Network Embedding Beyond Homophily
arxiv, 2022 Accepted to Transactions on Machine Learning ...
Zhong, Zhiqiang +3 more
openaire +3 more sources
Layer Information Similarity Concerned Network Embedding
Complexity, 2021 Great achievements have been made in network embedding based on single-layer networks. However, there are a variety of scenarios and systems that can be presented as multiplex networks, which can reveal more interesting patterns hidden in the data ...
Ruili Lu +4 more
doaj +1 more source
On distributed virtual network embedding with guarantees [PDF]
, 2000 To provide wide-area network services, resources from different infrastructure providers are needed. Leveraging the consensus-based resource allocation literature, we propose a general distributed auction mechanism for the (NP-hard) virtual network (VNET)
Esposito, Flavio +2 more
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