Predicting research trends with semantic and neural networks with an application in quantum physics.

ABSTRACT: The vast and growing number of publications in all disciplines of science cannot be comprehended by a single human researcher. As a consequence, researchers have to specialize in narrow subdisciplines, which makes it challenging to uncover scientific connections beyond the own field of research. Thus, access to structured knowledge from a large corpus of publications could help push the frontiers of science. Here, we demonstrate a method to build a semantic network from published scientific literature, which we call SemNet We use SemNet to predict future trends in research and to inspire personalized and surprising seeds of ideas in science. We apply it in the discipline of quantum physics, which has seen an unprecedented growth of activity in recent years. In SemNet, scientific knowledge

SUBMITTER: Krenn M 

PROVIDER: S-EPMC6994972 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature