Results 61 to 70 of about 9,217,308 (160)

Simple but Effective Compound Geometric Operations for Temporal Knowledge Graph Completion [PDF]

Temporal knowledge graph completion aims to infer the missing facts in temporal knowledge graphs. Current approaches usually embed factual knowledge into continuous vector space and apply geometric operations to learn potential patterns in temporal ...
Hu, Mengting, Cheng, Renhong, Xie, Yalan, Gao, Hang, Zhang, Linlin, Wang, Zhunheng, Ying, Rui, Wu, Jianfeng, Liu, Xiaoyi, Jiang, Ming   +9 more
core   +1 more source

Pre-trained Language Model for Temporal Knowledge Graph Completion

Journal of Pharmacy and Pharmacology Research
Large Language Models (LLMs) have been proven remarkable in natural language processing, which prompts numerous works on knowledge extraction, knowledge fusion, knowledge representation, and knowledge completion. Existing works mainly focus on static multi-relational knowledge graph (KG).
Wenying Feng, Jianming Li, Zhiqiang Zhang, Angxiao Zhao, Yan Jia, Zhaoquan Gu   +5 more
openaire   +1 more source

Semantic-Enhanced Knowledge Graph Completion

Knowledge graphs (KGs) serve as structured representations of knowledge, comprising entities and relations. KGs are inherently incomplete, sparse, and have a strong need for completion.
Anni Chen (17389327), Jiaxi Chen (4727637), Wenhong Zhao (10946617), Yingbo Wang (3701866), Shuo Yu (3276831), Xu Yuan (540430), Yiou Huang (20266308)   +6 more
core   +3 more sources

ContxE: Attention-based Context Aggregation for Temporal Knowledge Graph Completion

ContxE: Attention-based Context Aggregation for Temporal Knowledge Graph ...
Borui Cai (14042361), Yong Xiang (13101027), Longxiang Gao (13354656), Jiong Jin (13364769), Junfeng Wu (23234), Tom Luan (19534030)   +5 more
core  

Context-Aware Temporal Knowledge Graph Embedding

, 2019
Knowledge graph embedding (KGE) is an important technique used for knowledge graph completion (KGC). However, knowledge in practice is time-variant and many relations are only valid for a certain period of time.
Liu, Yu, Hua, Wen, Xin, Kexuan, Zhou, Xiaofang   +3 more
core   +1 more source

Knowledge Graph

, 2018
This Wikipedia entry describes the Knowledge Graph as a knowledge base by Google. It enhances the search engine's results by gathering information from a variety of sources.
Wikipedia, HostingInstitution
core   +1 more source

Dynamic link prediction: Using language models and graph structures for temporal knowledge graph completion with emerging entities and relations

Knowledge graphs (KGs) represent real-world facts through entities and relations. However, static KGs fail to capture continuously emerging entities and relations over time.
Ong, Ryan, Sun, Jiahao, Serban, Ovidiu, Guo, Yi Ke   +3 more
core   +1 more source

Idaho Completion Project’s Accelerated Retrieval Project Overview of the Pit 4 Non-Time Critical Removal Action [PDF]

, 2005
This paper presents an overview of the Accelerated Retrieval Project performed by the Idaho Completion Project at the Idaho National Laboratory (INL). Topics include an overall description of the process and methods that will retrieve, characterize, and ...
Arbon, R. E., Clements, T. L., Preussner, B. D.   +2 more
core  

Hierarchical Perceptual Graph Attention Network for Knowledge Graph Completion

Knowledge graph completion (KGC), the process of predicting missing knowledge through known triples, is a primary focus of research in the field of knowledge graphs.
Jianhao Zhang, Xuemei Liu, Wenhao Han, Hairui Li   +3 more
core   +1 more source

Reinforcement Learning-Based Temporal Knowledge Graph Reasoning for Predicting Chronic Gastritis Diagnosis and Treatment: Development and Validation Study. [PDF]

JMIR Med Inform
Qu X, Sun Z, Wang Y, Liu H, Yao L, Li D, Song G, Zhang R, Zhang X.   +8 more
europepmc   +1 more source