About Us
Make KGE Easier & Better
Our Mission
The knowledge graph stores a large amount of knowledge represented by symbolic triples. With the maturity of automatic extraction technology and a lot of human input, many high-quality knowledge graphs have been successfully constructed, and are used for search recommendation, intelligent question answering, root cause tracing, etc. Application tasks provide rich symbolic knowledge services. With the rise of deep learning, the algorithms of many downstream tasks are calculated based on vector space, and the symbolic knowledge service also brings additional tasks of symbolic knowledge representation and fusion to downstream tasks. Therefore, we developed the NeuralKG tool for general purpose of knowledge graph representation learning and easier applications.
OUR TEAM
NeuralKG Core Team
Wen Zhang
Huajun Chen
X.N.Chen
Clinical Psychologist
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Z.Yao
Clinical Psychologist
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M.Y.Chen
Clinical Psychologist
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Y.S.Zhu
Clinical Psychologist
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H.T.Y
Clinical Psychologist
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Y.F.Huang
Clinical Psychologist
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Z.Z.Xu
Clinical Psychologist
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J.Y.Xu
Clinical Psychologist
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