Expert Systems with Applications 36(2009)5173-5183 Contents lists available at ScienceDirect Expert Systems with Applications ELSEVIER journalhomepagewww.elsevier.com/locate/eswa A recommender system for research resources based on fuzzy linguistic modeling C Porcel, A.G. Lopez-Herrera, E. Herrera-Viedma Computer Science. University of jaen, 23071 Jaen, Spain dEpartment of Computer Science and Artificial Intelligence University of Granada, 18071, Granada, Spain ARTICLE IN FO A BSTRACT 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 uzzy linguistic modeling nd they need tools to assist them to obtain the required information Recommender systems are tools ulti-granular linguistic information Those 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 represen- tations 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 informa- tion. Similar problems are appearing in other frameworks, such as digital academic libraries, research offices business contacts etc. we focus on info access processes in technology transfer offices. The aim of this paper is to develop a recommender system for research resources based on fuzzy linguis- tic modeling. The system helps researchers and environment companies allowing them to obtain auto- matically 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 ne University of Granada and experimental results show that it ible and effective e 2008 Elsevier Ltd. All rights reserved. 1 Introduction Advice in the preparation of offers(management, spread and A Technology Transfer Office(TTO) is responsible for putting Support in the elaboration and negotiation of contracts with into action and managing the activities which generate knowledge companies. and technical and scientific collaboration, thus enhancing the Management of contacts. interrelation between researchers at the University and the entre- Technological offer (the elaboration preneurial world and their participation in various support pro- grammes designed to carry out research, development and n of the The advice in the creation of new businesses nnovation activities. the main mission in this office is to encour- Evaluation, protection and transfer of ownership rights both and help, from the University, the generation of knowledge intellectual and industria nd its spread and transfer to the society, with the aim of rapidly meeting society's needs and demands A graphical representation To fulfil these objectives and manage all the services, a Tto is of this mission is shown in Fig. 1(The Centre for Innovation, composed by a team of technicians that are experts in technology transfer. Each one manages a specific task, but all of them must To carry out its objectives, a tto runs a number of services provide information about research resources to the researchers hich we highlight the followings (The Centre for Innovation, and companies, that is bulletins, projects, calls, notices, events, congresses, courses, and so on. This task requires the selection by he expert of suitable researchers to deliver the information. In this Guidance for Research and Development(R&D)and Technology sources is contributing to that Tto experts not being able to spread Transfer funding. the information to the suitable users(both researchers and compa nies)in a simple and timely manner. Then Tto experts are in need of tools to help them cope with the large amount of information E-mail addresses: cporcelQujaenes(C Porcel), viedma@desai. ugr es (E. Herrera- available about research resources. A promising direction to im- prove the information access about research resources concerns 0957-4174/s- see front matter o 2008 Elsevier Ltd. All rights reserved. doi:10.1016eswa2008.06.03A recommender system for research resources based on fuzzy linguistic modeling C. Porcel a , A.G. López-Herrera a , E. Herrera-Viedma b,* aDepartment of Computer Science. University of Jaén, 23071 Jaén, Spain bDepartment of Computer Science and Artificial Intelligence University of Granada, 18071, Granada, Spain article info Keywords: Recommender systems Information filtering Fuzzy linguistic modeling Multi-granular linguistic information abstract 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 represen￾tations 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 informa￾tion. 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 linguis￾tic modeling. The system helps researchers and environment companies allowing them to obtain auto￾matically 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. 2008 Elsevier Ltd. All rights reserved. 1. Introduction A Technology Transfer Office (TTO) is responsible for putting into action and managing the activities which generate knowledge and technical and scientific collaboration, thus enhancing the interrelation between researchers at the University and the entre￾preneurial world and their participation in various support pro￾grammes designed to carry out research, development and innovation activities. The main mission in this office is to encour￾age and help, from the University, the generation of knowledge and its spread and transfer to the society, with the aim of rapidly meeting society’s needs and demands. A graphical representation of this mission is shown in Fig. 1 (The Centre for Innovation, XXXX). To carry out its objectives, a TTO runs a number of services which we highlight the followings (The Centre for Innovation, XXXX): Information (R&D bulletins, R&D&I, calls, notices, projects). Guidance for Research and Development (R&D) and Technology Transfer funding. Advice in the preparation of offers (management, spread and exploitation). Support in the elaboration and negotiation of contracts with companies. Management of contacts. Technological offer (the elaboration of the offer, spread and promotion). The advice in the creation of new businesses. Evaluation, protection and transfer of ownership rights both intellectual and industrial. To fulfil these objectives and manage all the services, a TTO is composed by a team of technicians that are experts in technology transfer. Each one manages a specific task, but all of them must provide information about research resources to the researchers and companies, that is bulletins, projects, calls, notices, events, congresses, courses, and so on. This task requires the selection by the expert of suitable researchers to deliver the information. In this task, we find a first problem, the large increase of research re￾sources is contributing to that TTO experts not being able to spread the information to the suitable users (both researchers and compa￾nies) in a simple and timely manner. Then TTO experts are in need of tools to help them cope with the large amount of information available about research resources. A promising direction to im￾prove the information access about research resources concerns 0957-4174/$ - see front matter 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.eswa.2008.06.038 * Corresponding author. E-mail addresses: cporcel@ujaen.es (C. Porcel), viedma@decsai.ugr.es (E. Herrera￾Viedma). Expert Systems with Applications 36 (2009) 5173–5183 Contents lists available at ScienceDirect Expert Systems with Applications journal homepage: www.elsevier.com/locate/eswa