Generative Transformer with Knowledge-Guided Decoding for Academic Knowledge Graph Completion

Xiangwen Liu, Shengyu Mao, Xiaohan Wang and Jiajun Bu ()
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Xiangwen Liu: College of Computer Science and Technology, Zhejiang University, Hangzhou 310007, China
Shengyu Mao: College of Computer Science and Technology, Zhejiang University, Hangzhou 310007, China
Xiaohan Wang: College of Computer Science and Technology, Zhejiang University, Hangzhou 310007, China
Jiajun Bu: College of Computer Science and Technology, Zhejiang University, Hangzhou 310007, China

Mathematics, 2023, vol. 11, issue 5, 1-12

Abstract: Academic knowledge graphs are essential resources and can be beneficial in widespread real-world applications. Most of the existing academic knowledge graphs are far from completion; thus, knowledge graph completion—the task of extending a knowledge graph with missing entities and relations—attracts many researchers. Most existing methods utilize low-dimensional embeddings to represent entities and relations and follow the discrimination paradigm for link prediction. However, discrimination approaches may suffer from the scaling issue during inference with large-scale academic knowledge graphs. In this paper, we propose a novel approach of a generative transformer with knowledge-guided decoding for academic knowledge graph completion. Specifically, we introduce generative academic knowledge graph pre-training with a transformer. Then, we propose knowledge-guided decoding, which leverages relevant knowledge in the training corpus as guidance for help. We conducted experiments on benchmark datasets for knowledge graph completion. The experimental results show that the proposed approach can achieve performance gains of 30 units of the MRR score over the baselines on the academic knowledge graph AIDA.

Keywords: knowledge graph; transformer; generation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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