Nov 20, 2020 · SNEGAN combines a generator with a signed random walker technique and a graph softmax function to generate fake links that are used to deceive ...
In this paper, we propose a novel generative adversarial nets learning framework (called SNEGAN) for signed network embedding, which tries to preserve link ...
SNEGAN combines a generator with a signed random walker technique and a graph softmax function to generate fake links that are used to deceive discriminator.
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Zihan Zhou, Yu Gu, Ge Yu. SNEGAN: Signed Network Embedding by Using Generative Adversarial Nets IEEE Transactions on Emerging Topics in Computational ...
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We propose a novel framework SNEA, which exploits the network structure and user attributes simultaneously for network representation learning. Experimental ...
SNEGAN: Signed Network Embedding by Using Generative Adversarial Nets · Multimorbidity prediction using link prediction · Incorporating Syntactic and Phonetic ...
SNEGAN: Signed Network Embedding by Using Generative Adversarial Nets. Article. Nov 2020. Ma Lijia · Yuchun Ma · Qiuzhen Lin · Maoguo Gong.
In this paper, we propose a novel generative adversarial nets learning framework (called SNEGAN) for signed network embedding, which ...
Ma, SNEGAN: Signed network embedding by using generative adversarial nets, IEEE Transactions on Emerging Topics in Computational Intelligence, с. 1; Ma ...