Results 251 to 260 of about 8,119,426 (288)

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
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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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Complete Fuzzy Knowledge Representation With Knowledge Graph Embedding

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy knowledge graph embedding (KGE) aims to represent uncertain facts for reliable reasoning and decision-making. While recent studies have begun to explore fine-grained fuzzy KGs that associate uncertainty with individual elements, existing approaches remain limited by (i) unreliable neighborhood aggregation that may amplify low-confidence noise ...
Haoning Li, Qinghua Huang
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Explaining Completions Produced by Embeddings of Knowledge Graphs

2019
Advanced question answering typically employs large-scale knowledge bases such as DBpedia or Freebase, and are often based on mappings from entities to real-valued vectors. These mappings, called embeddings, are accurate but very hard to explain to a human subject.
Andrey Ruschel, Arthur Colombini Gusmão, Gustavo Padilha Polleti, Fábio Gagliardi Cozman   +3 more
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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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Supervised Knowledge Aggregation for Knowledge Graph Completion

2022
Betz, Patrick, Meilicke, Christian, Stuckenschmidt, Heiner   +2 more
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