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

The corpus of scientific literature grows at an ever increasing speed. While this poses a severe challenge for human researchers, computer algorithms with access to a large body of knowledge could help make important contributions to science. Here, we demonstrate the development of a semantic network for quantum physics, denoted SEMNET, using 750,000 scientific papers and knowledge from books and Wikipedia. We use it in conjunction with an artificial neural network for predicting future research trends. Individual scientists can use SEMNET for suggesting and inspiring personalized, out-of-the-box ideas. Computer-inspired scientific ideas will play a significant role in accelerating scientific progress, and we hope that our work directly contributes to that important goal.