Fusing topology contexts and logical rules in language models for knowledge graph completion

• Main Authors: Lin, Qika, Mao, Rui, Liu, Jun, Xu, Fangzhi, Cambria, Erik
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Knowledge Graph Completion; Information Fusion
• Online Access: https://hdl.handle.net/10356/170544
• Institution: Nanyang Technological University

Knowledge graph completion (KGC) aims to infer missing facts based on the observed ones, which is significant for many downstream applications. Given the success of deep learning and pre-trained language models (LMs), some LM-based methods are proposed for the KGC task. However, most of them focus o...