Improving queries and representing heterogeneous information in Fuzzy Ontologies using multi-granular fuzzy linguistic modelling methods

2016 ◽  
Author(s):  
Juan Antonio Morente-Molinera ◽  
Ignacio Javier Perez ◽  
Francisco Javier Cabrerizo ◽  
Carlos Porcel ◽  
Enrique Herrera-Viedma
Keyword(s):  
Heterogeneous Information ◽  
Fuzzy Linguistic Modelling ◽  
Fuzzy Linguistic ◽  
Modelling Methods

scholarly journals Using Multi-granular Fuzzy Linguistic Modelling Methods to Represent Social Networks Related Information in an Organized Way

2020 ◽  
Vol 15 (2) ◽  
Author(s):  
Juan Antonio Morente-Molinera ◽  
Francisco Javier Cabrerizo ◽  
Sergio Alonso ◽  
María Ángeles Martínez ◽  
Enrique Herrera-Viedma
Keyword(s):  
Social Networks ◽  
Social Needs ◽  
Free Form ◽  
Free Text ◽  
Related Information ◽  
Fuzzy Linguistic Modelling ◽  
Novel Method ◽  
Fuzzy Linguistic ◽  
Modelling Methods ◽  
Extract Information

Social networks are the preferred mean for experts to share their knowledge and provide information. Therefore, it is one of the best sources that can be used for obtaining data that can be used for a high amount of purposes. For instance, determining social needs, identifying problems, getting opinions about certain topics, ... Nevertheless, this kind of information is difficult for a computational system to interpret due to the fact that the text is presented in free form and that the information that represents is imprecise. In this paper, a novel method for extracting information from social networks and represent it in a fuzzy ontology is presented. Sentiment analysis procedures are used in order to extract information from free text. Moreover, multi-granular fuzzy linguistic modelling methods are used for converting the information into the most suitable representation mean.

Fuzzy Linguistic Modelling in Multi Modal Human Computer Interaction

2013 ◽  
pp. 1481-1496
Author(s):  
Ilham N. Huseyinov
Keyword(s):  
Learning Styles ◽  
Human Computer Interaction ◽  
Cognitive Learning ◽  
Adaptation Strategy ◽  
Information Navigation ◽  
Fuzzy Linguistic Modelling ◽  
High Level ◽  
The Cost ◽  
Fuzzy Linguistic ◽  
Computer Interaction

The purpose of this chapter is to explore fuzzy logic based methodology for computing an adaptive interface in an environment of imperfect, vague, multimodal, complex nonlinear hyper information space. To this end, based on fuzzy linguistic modelling and fuzzy multi level granulation an adaptation strategy to cognitive/learning styles is presented. The granulated fuzzy if-then rules are utilized to adaptively map cognitive/learning styles of users to their information navigation and presentation preferences through natural language expressions. The important implications of this approach are that, first, uncertain and vague information is handled; second, a mechanism for approximate adaptation at a variety of granulation levels is provided; third, a qualitative linguistic model of adaptation is presented. The proposed approach is close to human reasoning and thereby lowers the cost of solution, and facilitates the design of human computer interaction systems with high level intelligence capability.

scholarly journals On Multi-granular Fuzzy Linguistic Modelling in Decision Making

2015 ◽  
Vol 55 ◽  
pp. 593-602 ◽  
Author(s):  
J.A. Morente-Molinera ◽  
I.J. Pérez ◽  
R. Ureña ◽  
E. Herrera-Viedma
Keyword(s):  
Decision Making ◽  
Fuzzy Linguistic Modelling ◽  
Fuzzy Linguistic
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