Name
Title | ||
|---|---|---|
ConvMB: Improving Convolution-Based Knowledge Graph Embeddings by Adopting Multi-Branch 3D Convolution Filters |
Abstract | ||
|---|---|---|
In this paper, we propose a novel embedding model, named ConvMB, for knowledge base completion. ConvE captures the potential semantic associations of the knowledge base by learning the local feature interactions among the same entry of the embeddings. ConvKB further makes full use of the global feature interactions among the same entries of the embeddings to get a better performance. CapsE gains i... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00060 | 2021 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom) |
Keywords | DocType | ISSN |
Knowledge Representation Learning,Convolutional Neural Network,Muti-branch 3D Convolution Filters | Conference | 2158-9178 |
ISBN | Citations | PageRank |
978-1-6654-3574-1 | 0 | 0.34 |
References | Authors | |
0 | 5 | |