Novel Recommendation-Based Approach for Multidisciplinary Development of Future Universities

Abstract

Multidisciplinary sustainable development is an important and complex system for comprehensive universities. Typically, a comprehensive university’s objective is to create a free, open, and diversified ecosystem of disciplines. Given finite available resources, e.g., funding or investment, configuring the formation of disciplines is critical. Understanding the interrelationships among different disciplines is challenging. Rather than directly wading through massive high-dimensional interrelated data, we judiciously formulate the cumbersome configurations of disciplines as a discipline recommendation problem. In this paper, we propose a novel data-driven approach to the configuration of disciplines based on a recommendation to predict and recommend an appropriate configuration of disciplines. The proposed approach exhibits good performance against standard metrics on real-world public data sets. It can be implemented as an attractive engine for constructing disciplines for universities.