Results 1 to 10 of about 30,602 (303)

A type-augmented knowledge graph embedding framework for knowledge graph completion [PDF]

Scientific Reports, 2023
Knowledge graphs (KGs) are of great importance to many artificial intelligence applications, but they usually suffer from the incomplete problem.
Peng He, Gang Zhou, Yao Yao, Zhe Wang, Hao Yang   +4 more
doaj   +2 more sources

An Approach to Knowledge Base Completion by a Committee-Based Knowledge Graph Embedding [PDF]

Applied Sciences, 2020
Knowledge bases such as Freebase, YAGO, DBPedia, and Nell contain a number of facts with various entities and relations. Since they store many facts, they are regarded as core resources for many natural language processing tasks.
Su Jeong Choi, Hyun-Je Song, Seong-Bae Park   +2 more
doaj   +2 more sources

Advances in Knowledge Graph Embedding Based on Graph Neural Networks [PDF]

Jisuanji kexue yu tansuo, 2023
As graph neural networks continue to develop, knowledge graph embedding methods based on graph neural networks are receiving increasing attention from researchers.
YAN Zhaoyao, DING Cangfeng, MA Lerong, CAO Lu, YOU Hao
doaj   +1 more source

Survey on Applications of Knowledge Graph Embedding in Recommendation Tasks [PDF]

Jisuanji kexue yu tansuo, 2022
Recommendation systems are designed to recommend personalized content to improve user experience. At present, the recommendation systems still face some challenges such as poor interpretability, cold start problem and serialized recommendation modeling ...
TIAN Xuan, CHEN Hangxue
doaj   +1 more source

Real-Time Semantic Data Flow Reasoning Based on Improved Multi-Embedding Space [PDF]

Jisuanji gongcheng, 2022
The joint use of semantic data flow processing engine and knowledge graph embedding representation learning can effectively improve the performance of real-time data stream reasoning and query.The existing knowledge representation learning models pay ...
GAO Feng, YAO Guangtao, GU Jinguang
doaj   +1 more source

HTINet2: herb-target prediction via knowledge graph embedding and residual-like graph neural network. [PDF]

Brief Bioinform
Duan P, Yang K, Su X, Fan S, Dong X, Zhang F, Li X, Xing X, Zhu Q, Yu J, Zhou X.   +10 more
europepmc   +2 more sources

QubitE:Qubit Embedding for Knowledge Graph Completion [PDF]

Jisuanji kexue, 2023
The knowledge graph completion task completes the knowledge graph by predicting missing facts in the knowledge graph.The quantum-based knowledge graph embedding(KGE) model uses variational quantum circuits to score triples by mea-suring the probability ...
LIN Xueyuan, E Haihong , SONG Wenyu, LUO Haoran, SONG Meina
doaj   +1 more source

WeExt: A Framework of Extending Deterministic Knowledge Graph Embedding Models for Embedding Weighted Knowledge Graphs

IEEE Access, 2023
With the further development of knowledge graphs, many weighted knowledge graphs (WKGs) have been published and greatly promote various applications. However, current deterministic knowledge graph embedding algorithms cannot encode weighted knowledge ...
Kong Wei Kun, Xin Liu, Teeradaj Racharak, Guanqun Sun, Jianan Chen, Qiang Ma, Le-Minh Nguyen   +6 more
doaj   +1 more source

Comprehensive Survey of Loss Functions in Knowledge Graph Embedding Models [PDF]

Jisuanji kexue, 2023
Due to its rich and intuitive expressivity,knowledge graph has received much attention of many scholars. A lot of works have been accumulated in knowledge graph embedding.
SHEN Qiuhui, ZHANG Hongjun, XU Youwei, WANG Hang, CHENG Kai
doaj   +1 more source

Language Model Guided Knowledge Graph Embeddings

IEEE Access, 2022
Knowledge graph embedding models have become a popular approach for knowledge graph completion through predicting the plausibility of (potential) triples.
Mirza Mohtashim Alam, Md Rashad Al Hasan Rony, Mojtaba Nayyeri, Karishma Mohiuddin, M. S. T. Mahfuja Akter, Sahar Vahdati, Jens Lehmann   +6 more
doaj   +1 more source