Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (3): 251-256.doi: 10.11896/jsjkx.221200080

• Artificial Intelligence • Previous Articles     Next Articles

Knowledge Graph Embedding Model with Entity Description on Cement Manufacturing Domain

ZHOU Honglin, SONG Huazhu, ZHANG Juan   

  1. School of Computer Science and Technology,Wuhan University of Technology,Wuhan 430070,China
  • Received:2022-12-12 Revised:2023-06-08 Online:2024-03-15 Published:2024-03-13
  • About author:ZHOU Honglin,born in 1999,postgra-duate.Her main research interests include knowledge graph and reinforcement learning.SONG Huazhu,born in 1970,Ph.D,associate professor,master supervisor,is a senior member of CCF(No.12201S).Her main research interests include artificial intelligent and data mining,semantic and knowledge abstraction.

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Abstract: To address the problem that many knowledge graph embedding models lack the consideration of semantic information when performing knowledge embedding and cannot extract the semantic information of entities specialized in cement manufactu-ring domain well.The entity description text is added to the embedding work of cement manufacturing domain knowledge graph(CMFKG),and the knowledge graph embedding with entity description model(KGEED) is proposed,which adopts the TransE model to get the embedding of structural information of CMFKG.The CNN-based entity description embedding module is used to obtain the semantic-based embedding of CMFKG,and the triples of structural information embedding and semantic information embedding are fused with CNN,so that the rich entity description text information of the knowledge graph in cement manufactu-ring domain can be well considered.Experiments show that the model achieves good results in the embedding work of the know-ledge graph in cement manufacturing domain.

Key words: Cement manufacturing domain, Knowledge graph, Entity description embedding, Entity link

CLC Number: 

  • TP181
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