Improving Knowledge Graph Quality with Network Representation Learning

Knowledge graphs serve as an essential source for many tasks in data mining, artificial intelligence, and interdisciplinary challenges such as entity disambiguation, fact checking, and computational journalism. However, real-world knowledge graphs are far from perfect, so it remains a crucial task to improve the quality and completeness of these essential tools.