A Hybrid Recommender System for the Selective Dissemination of Research Resources in a Technology Transfer Office

A Hybrid Recommender System for the Selective Dissemination of Research Resources in a Technology Transfer Office  　

C. Porcel^a, , , A. Tejeda-Lorente^b, M.A. Martínez^b and E. Herrera-Viedma^b, 

^a University of Jaén, Department of Computer Science, Jaén, Spain

^b University of Granada, Department of Computer Science and Artificial Intelligence, Granada, Spain

Received 14 December 2009;  

revised 6 June 2011;  

accepted 22 August 2011.  

Available online 6 September 2011. 

Abstract

Recommender systems could be used to help users in their access processes to relevant information. Hybrid recommender systems represent a promising solution for multiple applications. In this paper we propose a hybrid fuzzy linguistic recommender system to help the Technology Transfer Office staff in the dissemination of research resources interesting for the users. The system recommends users both specialized and complementary research resources and additionally, it discovers potential collaboration possibilities in order to form multidisciplinary working groups. Thus, this system becomes an application that can be used to help the Technology Transfer Office staff to selectively disseminate the research knowledge and to increase its information discovering properties and personalization capacities in an academic environment.

Keywords: Recommender systems; Fuzzy linguistic modeling; Technology transfer office