Results 321 to 330 of about 468,662 (346)

Multi-perspective Improvement of Knowledge Graph Completion with Large Language Models

International Conference on Language Resources and Evaluation
Knowledge graph completion (KGC) is a widely used method to tackle incompleteness in knowledge graphs (KGs) by making predictions for missing links. Description-based KGC leverages pre-trained language models to learn entity and relation representations ...
Derong Xu, Ziheng Zhang, Zhenxi Lin, Xian Wu, Zhihong Zhu, Tong Xu, Xiangyu Zhao, Yefeng Zheng, Enhong Chen   +8 more
semanticscholar   +1 more source

Halal or Not: Knowledge Graph Completion for Predicting Cultural Appropriateness of Daily Products

IEEE Access
The growing demand for halal cosmetic products has exposed significant challenges, especially in Muslim-majority countries. Recently, various machine learning-based strategies, e.g., image-based methods, have shown remarkable success in predicting the ...
Van Thuy Hoang, Tien-Bach-Thanh do, Jinho Seo, Seung Charlie Kim, Luong Vuong Nguyen, Duong Nguyen Minh Huy, Hyeon-Ju Jeon, O-Joun Lee   +7 more
semanticscholar   +1 more source

Contextualization Distillation from Large Language Model for Knowledge Graph Completion

Findings
While textual information significantly enhances the performance of pre-trained language models (PLMs) in knowledge graph completion (KGC), the static and noisy nature of existing corpora collected from Wikipedia articles or synsets definitions often ...
Dawei Li, Zhen Tan, Tianlong Chen, Huan Liu   +3 more
semanticscholar   +1 more source

LLM-based Multi-Level Knowledge Generation for Few-shot Knowledge Graph Completion

International Joint Conference on Artificial Intelligence
Knowledge Graphs (KGs) are pivotal in various NLP applications but often grapple with incompleteness, especially due to the long-tail problem where infrequent, unpopular relationships drastically reduce the KG completion performance.
Qian Li, Zhuo Chen, Cheng Ji, Shiqi Jiang, Jianxin Li   +4 more
semanticscholar   +1 more source

Advanced Topic: Knowledge Graph Completion

2019
With the possible exception of good data collection and ontology design, information extraction and entity resolution are the two most important data-driven steps in a domain-specific knowledge graph construction pipeline. Yet, it is very rarely the case that the story ends there.
openaire   +1 more source

Knowledge Graphs 2023 - 6.3 Knowledge Graph Completion

2023
Sack, Harald, Tan, Mary Ann
openaire   +1 more source

Graph Structure Enhanced Pre-Training Language Model for Knowledge Graph Completion

IEEE Transactions on Emerging Topics in Computational Intelligence
A vast amount of textual and structural information is required for knowledge graph construction and its downstream tasks. However, most of the current knowledge graphs are incomplete due to the difficulty of knowledge acquisition and integration ...
Huashi Zhu, Dexuan Xu, Yu Huang, Zhi Jin, Weiping Ding, Jiahui Tong, Guoshuang Chong   +6 more
semanticscholar   +1 more source

Supervised Knowledge Aggregation for Knowledge Graph Completion

2022
Betz, Patrick, Meilicke, Christian, Stuckenschmidt, Heiner   +2 more
openaire   +1 more source

Knowledge Graph Completion Technology Research

2022 International Conference on Computing, Robotics and System Sciences (ICRSS), 2022
Yongqi Shi, Yiwei Lu, Ruopeng Yang, Yuantao Yang   +3 more
openaire   +1 more source

Chain of History: Learning and Forecasting with LLMs for Temporal Knowledge Graph Completion

arXiv.org
Temporal Knowledge Graph Completion (TKGC) is a complex task involving the prediction of missing event links at future timestamps by leveraging established temporal structural knowledge.
Ruilin Luo, Tianle Gu, Haoling Li, Junzhe Li, Zicheng Lin, Jiayi Li, Yujiu Yang   +6 more
semanticscholar   +1 more source