Different Proposals to Improve the Accuracy of Fuzzy Linguistic Modeling

2000 ◽  
pp. 189-221 ◽  
Author(s):  
Oscar Cordón ◽  
Francisco Herrera ◽  
María José Jesus ◽  
Pedro Villar ◽  
Igor Zwir
Keyword(s):  
Linguistic Modeling ◽  
Fuzzy Linguistic

A recommender system for research resources based on fuzzy linguistic modeling

2009 ◽  
Vol 36 (3) ◽  
pp. 5173-5183 ◽  
Author(s):  
C. Porcel ◽  
A.G. López-Herrera ◽  
E. Herrera-Viedma
Keyword(s):  
Recommender System ◽  
Linguistic Modeling ◽  
Fuzzy Linguistic ◽  
Research Resources

Fuzzy Linguistic Modeling of the Regulation of Drosophila Segmentation Genes

BIOPHYSICS ◽  
2021 ◽  
Vol 66 (1) ◽  
pp. 40-58
Author(s):  
A. A. Makashov ◽  
E. M. Myasnikova ◽  
A. V. Spirov
Keyword(s):  
Segmentation Genes ◽  
Linguistic Modeling ◽  
Fuzzy Linguistic

scholarly journals Trust Based Fuzzy Linguistic Recommender Systems as Reinforcement for Personalized Education in the Field of Oral Surgery and Implantology

2020 ◽  
Vol 15 (3) ◽  
Author(s):  
Carlos Porcel ◽  
Julio Herce-Zelaya ◽  
Juan Bernabé-Moreno ◽  
Álvaro Tejeda-Lorente ◽  
Enrique Herrera-Viedma
Keyword(s):  
Recommender Systems ◽  
Oral Surgery ◽  
Academic Environment ◽  
Web Technologies ◽  
Personalized Services ◽  
Personalized Education ◽  
Linguistic Modeling ◽  
Teaching Learning ◽  
Fuzzy Linguistic ◽  
Trust Information

The rapid advances in Web technologies are promoting the development of new pedagogic models based on virtual teaching. In this framework, personalized services are necessary. Recommender systems can be used in an academic environment to assist users in their teaching-learning processes. In this paper, we present a trust based recommender system, adopting a fuzzy linguistic modeling, that provides personalized activities to students in order to reinforce their education, and applied it in the field of oral surgery and implantology. We don’t take into account users with similar ratings history but users in which each user can trust and we provide a method to aggregate the trust information. This system can be used in order to aid professors to provide students with a personalized monitoring of their studies with less effort. The results obtained in the experiments proved to be satisfactory.

A model to represent users trust in recommender systems using ontologies and fuzzy linguistic modeling

2015 ◽  
Vol 311 ◽  
pp. 102-118 ◽  
Author(s):  
C. Martinez-Cruz ◽  
C. Porcel ◽  
J. Bernabé-Moreno ◽  
E. Herrera-Viedma
Keyword(s):  
Recommender Systems ◽  
Linguistic Modeling ◽  
Fuzzy Linguistic

A Fuzzy Linguistic Extended LibQUAL+ Model to Assess Service Quality in Academic Libraries

2017 ◽  
Vol 16 (01) ◽  
pp. 225-244 ◽  
Author(s):  
F. J. Cabrerizo ◽  
J. López-Gijón ◽  
M. A. Martínez ◽  
J. A. Morente-Molinera ◽  
E. Herrera-Viedma
Keyword(s):  
Service Quality ◽  
Natural Language ◽  
Academic Libraries ◽  
Quality Evaluation ◽  
Library Services ◽  
Service Levels ◽  
Standard Representation ◽  
Linguistic Modeling ◽  
Fuzzy Linguistic

LibQUAL+ model is the best-known method for the quality evaluation of library services, but it has two major drawbacks. First, to measure the quality, it is devised on a cardinal scale: the service levels range from 1 to 9. However, the standard representation of the concepts used by humans for communication is the natural language and, hence, users should express their judgments by using words instead of numbers. Second, it considers that all users’ opinions are equally important. Nevertheless, users do not play an equal role in assessing the service quality, i.e., the opinion given by some users should be more relevant than the opinion provided by others. To solve these drawbacks, we present an extended LibQUAL+ model representing the users’ perceptions by using a fuzzy linguistic modeling and taking into account that users’ opinions on the library services are not equally important.

A model for the integration of e-financial services questionnaires with SERVQUAL scales under fuzzy linguistic modeling

2012 ◽  
Vol 39 (14) ◽  
pp. 11535-11547 ◽  
Author(s):  
Ramón A. Carrasco ◽  
Francisco Muñoz-Leiva ◽  
Juan Sánchez-Fernández ◽  
Francisco J. Liébana-Cabanillas
Keyword(s):  
Financial Services ◽  
Linguistic Modeling ◽  
Fuzzy Linguistic
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