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Harmonizing Human Insights and AI Precision: Hand in Hand for Advancing Knowledge Graph Task
May 16, 2024, 4:42 a.m. | Shurong Wang, Yufei Zhang, Xuliang Huang, Hongwei Wang
cs.LG updates on arXiv.org arxiv.org
Abstract: Knowledge graph embedding (KGE) has caught significant interest for its effectiveness in knowledge graph completion (KGC), specifically link prediction (LP), with recent KGE models cracking the LP benchmarks. Despite the rapidly growing literature, insufficient attention has been paid to the cooperation between humans and AI on KG. However, humans' capability to analyze graphs conceptually may further improve the efficacy of KGE models with semantic information. To this effect, we carefully designed a human-AI team (HAIT) …
abstract arxiv attention benchmarks cs.ai cs.lg embedding graph human insights knowledge knowledge graph link prediction literature precision prediction type
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