Equipping machines with comprehensive knowledge of the world's entities and
their relationships has been a long-standing goal of AI. Over the last decade,
large-scale knowledge bases, also known as knowledge graphs, have been
automatically constructed from web contents and text sources, and have become a
key asset for search engines. This machine knowledge c
本研究论文基于最近对知识图谱（KG）和自然语言处理（NLP）的研究文献的调查，从企业环境的选定应用场景出发，探讨了这种组合所产生的协同效应。论文涵盖了 KG 构建、推理以及基于 KG 的 NLP 任务的各种方法。除了解释创新的企业用例外，我们还评估了它们在实际应用中的成熟度，并展望了未来的新兴应用领域。