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Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph Reasoning
March 19, 2024, 4:42 a.m. | Markus J. Buehler
cs.LG updates on arXiv.org arxiv.org
Abstract: Using generative Artificial Intelligence (AI), we transformed a set of 1,000 scientific papers in the area of biological materials into detailed ontological knowledge graphs, revealing their inherently scale-free nature. Using graph traversal path detection between dissimilar concepts based on combinatorial ranking of node similarity and betweenness centrality, we reveal deep insights into unprecedented interdisciplinary relationships that can be used to answer queries, identify gaps in knowledge, and propose never-before-seen material designs and their behaviors. One …
abstract artificial artificial intelligence arxiv concepts cond-mat.mes-hall cond-mat.mtrl-sci cond-mat.soft cs.ai cs.cl cs.lg detection discovery extraction free generative generative artificial intelligence graph graph-based graphs intelligence intelligent knowledge knowledge graphs materials multimodal nature papers path ranking reasoning representation scale scientific scientific discovery set type
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