Literature-based Hypothesis Generation: Predicting the evolution of scientific literature to support scientists

Tarek R. Besold, Uchenna Akujuobi, Samy Badreddine, Jihun Choi, Hatem Elshazly, Frederick Gifford, Chrysa Iliopoulou, Kana Maruyama, Kae Nagano, Pablo Sanchez Martin, Thiviyan Thanapalasingam, Alessandra Toniato, Christoph Wehner

Keywords: AI, machine learning, science, hypothesis generation, literature, knowledge graphs, explainability

TL;DR: Introducing work towards building a fit-for-use hypothesis-generation system taking scientific literature as input and providing novel research hypotheses plus accompanying explanatory information as output.

Confirmation Of Submission Requirements: I submit an abstract. It uses the template provided on the submission page and is no longer than 2 pages.

Submission Number: 272