Results 51 to 60 of about 244,866 (345)

Quaternion Knowledge Graph Embeddings

CoRR, 2019
Accepted by NeurIPS ...
Shuai Zhang 0007, Yi Tay, Lina Yao 0001, Qi Liu 0049   +3 more
openaire   +3 more sources

Binarized Knowledge Graph Embeddings [PDF]

, 2019
Tensor factorization has become an increasingly popular approach to knowledge graph completion(KGC), which is the task of automatically predicting missing facts in a knowledge graph. However, even with a simple model like CANDECOMP/PARAFAC(CP) tensor decomposition, KGC on existing knowledge graphs is impractical in resource-limited environments, as a ...
Koki Kishimoto, Katsuhiko Hayashi 0001, Genki Akai, Masashi Shimbo, Kazunori Komatani   +4 more
openaire   +2 more sources

Embedding models for episodic knowledge graphs [PDF]

Journal of Web Semantics, 2019
26 ...
Yunpu Ma, Volker Tresp, Erik A. Daxberger   +2 more
openaire   +2 more sources

Relation path embedding in knowledge graphs [PDF]

Neural Computing and Applications, 2018
Large-scale knowledge graphs have currently reached impressive sizes; however, they are still far from complete. In addition, most existing methods for knowledge graph completion only consider the direct links between entities, ignoring the vital impact of the semantics of relation paths.
Xixun Lin, Yanchun Liang 0001, Fausto Giunchiglia, Xiaoyue Feng, Renchu Guan   +4 more
openaire   +3 more sources

Efficiently embedding dynamic knowledge graphs

Knowledge-Based Systems, 2022
46 ...
Tianxing Wu 0001, Arijit Khan 0001, Melvin Yong, Guilin Qi, Meng Wang 0009   +4 more
openaire   +3 more sources

Knowledge Graph Embedding via Metagraph Learning

, 2021
Knowledge graph embedding aims to represent entities and relations in a continuous feature space while preserving the structure of a knowledge graph.
Joyce Jiyoung Whang, Chanyoung Chung, Chung, Chanyoung, Whang, Joyce Jiyoung   +3 more
core   +1 more source

TeAST: Temporal Knowledge Graph Embedding via Archimedean Spiral Timeline

Annual Meeting of the Association for Computational Linguistics, 2023
Temporal knowledge graph embedding (TKGE) models are commonly utilized to infer the missing facts and facilitate reasoning and decision-making in temporal knowledge graph based systems.
Jiang Li, Xiangdong Su, Guanglai Gao
semanticscholar   +1 more source

Knowledge Graph Embedding Based Collaborative Filtering

IEEE Access, 2020
Along with the rapidly increasing massive online data, recommender systems have been used as an effective approach for filtering useful information, which have been widely adopted in many web applications.
Yuhang Zhang, Jun Wang, Jie Luo
doaj   +1 more source

HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding

Conference on Empirical Methods in Natural Language Processing, 2018
Knowledge Graph (KG) embedding has emerged as an active area of research resulting in the development of several KG embedding methods. Relational facts in KG often show temporal dynamics, e.g., the fact (Cristiano_Ronaldo, playsFor, Manchester_United) is
S. Dasgupta, Swayambhu Nath Ray, P. Talukdar   +2 more
semanticscholar   +1 more source

KGvec2go -- Knowledge Graph Embeddings as a Service

CoRR, 2020
In this paper, we present KGvec2go, a Web API for accessing and consuming graph embeddings in a light-weight fashion in downstream applications. Currently, we serve pre-trained embeddings for four knowledge graphs. We introduce the service and its usage, and we show further that the trained models have semantic value by evaluating them on multiple ...
Portisch, Jan, Hladik, Michael, Paulheim, Heiko   +2 more
openaire   +4 more sources