Results 261 to 270 of about 35,565 (288)

Supervised Knowledge Aggregation for Knowledge Graph Completion

, 2022
We explore data-driven rule aggregation based on latent feature representations in the context of knowledge graph completion. For a given query and a collection of rules obtained by a symbolic rule learning system, we propose end-to-end trainable ...
Betz, Patrick, Meilicke, Christian, Stuckenschmidt, Heiner   +2 more
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Conflict-aware multilingual knowledge graph completion

Knowledge-Based Systems, 2023
Knowledge graph completion (KGC), a task that aims at predicting missing links with existing information inside a knowledge graph (KG), has emerged as a popular research area in recent years. While many existing works have demonstrated effectiveness on a
Weihang Zhang, Ovidiu Şerban, Yike Guo   +2 more
exaly   +2 more sources

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Knowledge Graph Completion via Complete Attention between Knowledge Graph and Entity Descriptions

Proceedings of the 3rd International Conference on Computer Science and Application Engineering, 2019
The objective of learning representation of knowledge graph is assumed to encode both entities and relations into a continuous low-dimensional vector space. Previous methods usually represent the same entity in different triples with the same representation.
Minjun Zhao, Yawei Zhao, Bing Xu
openaire   +1 more source

XLNet For Knowledge Graph Completion

2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM), 2021
As the one of databases in artificial intelligence systems, knowledge graph has been widely used nowadays. Although the number of entities in current knowledge graphs has reached tens of millions or even billions level, directed cyclic graphs of their relations and entities composition were still relatively sparse.
Jie Liu, Xitong Ning, Wansong Zhang
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A survey of few-shot knowledge graph completion

Journal of Intelligent & Fuzzy Systems, 2023
With the continuous development of knowledge graph completion (KGC) technology, the problem of few-shot knowledge graph completion (FKGC) is becoming increasingly prominent. Traditional methods for KGC are not effective in addressing this problem due to the lack of sufficient data samples. Therefore, completing the task of knowledge graph with few-shot
Chaoqin Zhang, Ting Li, Yifeng Yin, Jiangtao Ma, Yong Gan, Yanhua Zhang, Yaqiong Qiao   +6 more
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Modeling path information for knowledge graph completion

Neural Computing and Applications, 2021
Knowledge graphs (KGs) store real-world information in the form of graphs consisting of relationships between entities and have been widely used in the Semantic Web community since it is readable by machines. However, most KGs are known to be very incomplete.
Ying Shen 0001, Dagang Li 0001, Nan Du 0001   +2 more
openaire   +1 more source

A Contextualized Entity Representation for Knowledge Graph Completion

2020
Knowledge graphs (KGs) have achieved great success in many AI-related applications in the past decade. Although KGs contain billions of real facts, they are usually not complete. This problem arises to the task of missing link prediction whose purpose is to perform link prediction between entities.
Fei Pu, Bailin Yang, Jianchao Ying, Lizhou You, Chenou Xu   +4 more
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A comprehensive overview of knowledge graph completion

Knowledge-Based Systems, 2022
Tong Shen, Fu Zhang 0001, Jingwei Cheng
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A survey of inductive knowledge graph completion

Neural Computing and Applications, 2023
Xinyu Liang, Guannan Si, Jianxin Li, Pengxin Tian, Zhaoliang An, Fengyu Zhou   +5 more
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