Exploring the Intersection of Large Language Models and Knowledge Graphs: A Special Issue

In recent years, the construction and evaluation of Knowledge Graphs (KGs) have gained significant attention due to their ability to support virtual assistants, search and recommendations on the web, and organization of data for large companies. However, the methods used to build these KGs can result in high sparsity and inaccuracies, making the evaluation of their quality essential. With the rise of Large Language Models (LLMs), there is an opportunity to advance KG construction and evaluation, but also challenges, such as the potential for LLMs to generate misinformation. This special issue invites researchers to explore the intersection of LLMs and KGs, focusing on using LLMs within KG construction systems, evaluating KG quality, and applying quality control systems to empower KG and LLM interactions. Topics include efficient solutions for deploying LLMs on large-scale KGs, quality assessment over temporal and dynamic KGs, and error detection and correction mechanisms. Submissions are encouraged before September 1, 2024, with an estimated publication date of January 15, 2025.