This workflow automates the process of building a comprehensive knowledge graph from academic research papers. It is designed to run daily, fetching recent papers related to a chosen domain such as artificial intelligence from sources like Semantic Scholar and arXiv. The workflow extracts key information from each paper, including concepts, methods, datasets, research questions, and findings, using AI-powered parsing. It then constructs a structured graph of the entities and their relationships, such as authors, concepts, and methodologies, and updates a neo4j database accordingly. This setup is ideal for researchers, universities, or research institutions aiming to maintain an up-to-date, interconnected knowledge base of scientific literature for easier retrieval, analysis, and discovery.
Automated Academic Knowledge Graph Builder
Node Count | 6 – 10 Nodes |
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Nodes Used | code, n8n-nodes-pdfvector.pdfVector, neo4j, openAi, postgres, scheduleTrigger, stickyNote |
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