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2015. Semantically Smooth Knowledge Graph Embedding. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th ...
The key idea of SSE is to take full advantage of additional semantic information and enforce theembedding space to be semantically smooth, i.e., ...
Dec 9, 2016 · The key idea of SSE is to take full advantage of additional semantic information and enforce the embedding space to be semantically smooth, i.e. ...
This paper considers the problem of embedding Knowledge Graphs (KGs) consisting of entities and relations into low-dimensional vector spaces.
Abstract—This paper considers the problem of embedding Knowledge Graphs (KGs) consisting of entities and relations into low-dimensional vector spaces.
Embedding of a knowledge graph. The vector representation of the entities and relations can be used for different machine learning applications.
Sep 1, 2015 · Semantically Smooth Knowledge Graph Embedding. Introduction. Background. Background. Knowledge Graph (KG): A multi-relational directed graph.
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Jul 31, 2023 · This vision paper discusses the existing algorithms for KG completion based on the variations for generating KG embeddings.
Missing: Smooth | Show results with:Smooth
Depending on the type of scoring function, there are two categories of embedding models: translational dis- tance models and semantic matching models.
"Semantically Smooth Knowledge Graph Embedding". ACL 2015. paper. (TransD) Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, Jun Zhao. "Knowledge Graph Embedding ...