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pro vyhledávání: '"Shangbin Feng"'
Current Graph Neural Networks (GNNs) suffer from the over-smoothing problem, which results in indistinguishable node representations and low model performance with more GNN layers. Many methods have been put forward to tackle this problem in recent y
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eff62ba7b4002f847fb1dcf840113e1a
http://arxiv.org/abs/2208.09027
http://arxiv.org/abs/2208.09027
Autor:
Zhaoxuan Tan, Zilong Chen, Shangbin Feng, Qingyue Zhang, Qinghua Zheng, Jundong Li, Minnan Luo
Knowledge Graph Embeddings (KGE) aim to map entities and relations to low dimensional spaces and have become the \textit{de-facto} standard for knowledge graph completion. Most existing KGE methods suffer from the sparsity challenge, where it is hard
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94b181d33ac9afa909b209070bd1ccdd
Publikováno v:
CIKM
Twitter has become a vital social media platform while an ample amount of malicious Twitter bots exist and induce undesirable social effects. Successful Twitter bot detection proposals are generally supervised, which rely heavily on large-scale datas
Publikováno v:
CIKM
Twitter has become a major social media platform since its launching in 2006, while complaints about bot accounts have increased recently. Although extensive research efforts have been made, the state-of-the-art bot detection methods fall short of ge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99c1606a6a4c58ee08f2175b94911e60
Twitter bot detection has become an important and challenging task to combat misinformation and protect the integrity of the online discourse. State-of-the-art approaches generally leverage the topological structure of the Twittersphere, while they n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::325ffbf8caccbf65c2800134eafec8bf