Enhancing recommender systems development with human, social, cultural and organizational factors

Abstract

Recommender Systems (RS) aim at suggesting filtered Web information adapted to the needs or interests of users by predicting their access behavior using a certain strategy or algorithm. The creation of RS is usually approached focusing mostly on user behavior modeling, while the recommendation engine often neglects critical, non-technical aspects of software systems development. Conceiving a RS primarily as a self-contained or part of a Web-application, the present paper utilizes the SpiderWeb methodology and takes into account important requirements that result from human, cultural, social and organizational factors (HSCO) so as to drive the RS development activities.