A Reusable Methodology for the Instantiation of Social Recommender Systems

Abstract

Social recommender systems exploit the social knowledge available in social networks to provide accurate recommendations. However, their instantiation is not straightforward due to its complexity. To alleviate this development complexity, we propose a methodology based on templates that conceptualize the behavior of such applications and can be reused to create several social recommender applications in social networks. This development methodology comprises not only templates but also a generic architecture named ARISE and a collection of software components that provide the required functionality. We prove that our social templates speed up and facilitate the development process, and demonstrate the viability of our generic architecture in two different case studies.