Formalising Hypothesis Virtues in Knowledge Graphs: A General Theoretical Framework and its Validation in Literature-Based Discovery Experiments

We introduce an approach to discovery informatics that uses knowledge graphs as the essential representation structure. In the perspective of our approach, knowledge graphs correspond to hypotheses. We present a framework for formalising so called hypothesis virtues within knowledge graphs. The framework is based on a classic work in philosophy of science, and naturally progresses from mostly informative foundational notions to actionable specifications of measures corresponding to particular virtues. These measures can consequently be used to determine refined sub-sets of knowledge graphs that have large relative potential for making discoveries. We validate the proposed framework by experiments in literature-based discovery. The experiments have demonstrated the utility of our work and its superiority w.r.t. related approaches.