CS-KG 2.0

The rapid evolution of AI and the increased accessibility of scientific articles through open access marks a pivotal moment in research. Nonetheless, a significant challenge remains: dealing with the overwhelming number of scientific papers published each year. The vast quantity of text, often found in hard-to-parse PDF files, poses significant challenges for AI technologies. A promising solution is the use of knowledge graphs, which provide structured, interconnected, and formalized frameworks that improve the capabilities of AI systems to integrate information from scientific literature. This paper presents the last version of the Computer Science Knowledge Graph (CS-KG 2.0), an extensive knowledge base generated from 15 million research papers. CS-KG 2.0 describes 25 million entities linked by 67 million relationships, offering a nuanced representation of the scientific knowledge within the field of computer science. This innovative resource facilitates new research opportunities in key areas such as analysis and forecasting of research trends, hypothesis generation, smart literature search, automatic production of literature review, and scientific question-answering