iPath: Forecasting the Pathway to Impact.

Forecasting the success of scientific work has been attracting extensive research attention in the recent years. It is often of key importance to foresee the pathway to impact for scholarly entities for (1) tracking research frontier, (2) invoking an early intervention and (3) proactively allocating research resources. Many recent progresses have been seen in modeling the longterm scientific impact for point prediction. However, challenges still remain when it comes to forecasting the impact pathway. In this paper, we propose a novel predictive model to collectively achieve a set of design objectives to address these challenges, including prediction consistency and parameter smoothness. Extensive empirical evaluations on real scholarly data validate the effectiveness of the proposed model.