A Recommender System For Research Resources Based On Fuzzy Linguistic Modeling

摘要

Nowadays, the increasing popularity of Internet has led to an abundant amount of information created and delivered over electronic media. It causes the information access by the users is a complex activity and they need tools to assist them to obtain the required information. Recommender systems are tools whose objective is to evaluate and filter the great amount of information available in a specific scope to assist the users in their information access processes. Another obstacle is the great variety of representations of information, specially when the users take part in the process, so we need more flexibility in the information processing. The fuzzy linguistic modeling allows to represent and handle flexible information. Similar problems are appearing in other frameworks, such as digital academic libraries, research offices, business contacts, etc. We focus on information access processes in technology transfer offices. The aim of this paper is to develop a recommender system for research resources based on fuzzy linguistic modeling. The system helps researchers and environment companies allowing them to obtain automatically information about research resources (calls or projects) in their interest areas. It is designed using some filtering tools and a particular fuzzy linguistic modeling, called multi-granular fuzzy linguistic modeling, which is useful when we have to assess different qualitative concepts. The system is working in the University of Granada and experimental results show that it is feasible and effective.