Quantum link prediction in complex networks

Predicting new links in physical, biological, social, or technological networks has a significant scientific and societal impact. Path-based link prediction methods utilize the explicit counting of even- odd-length paths between nodes to quantify score function infer unobserved links. Here, we propose quantum algorithm for path-based using controlled continuous-time walk encode even odd scores. Through classical simulations on few real networks, confirm that scoring performs similarly other predictors. In brief complexity analysis identify potential our approach uncovering speedup prediction.