Paper Info
Title
A category-based information filtering approach based on interval type 2 fuzzy sets.
Abstract
Category-based information filtering is ground on the representation of user preferences according to a set of categories of similar items. The use of type 1 fuzzy sets provides a good method to represent categories when only one static interpretation of them is considered. This representation is not enough when documents do not have the same meaning for two different users because there are some degrees of subjectivity. On the other hand, type 2 fuzzy sets have been successfully applied to manage uncertainty more effectively than type-1 fuzzy sets in several environments. This paper presents a method to manage efficiently uncertainties in the filtering process in environments where there is a constant flow of new information (news, e-mail, etc.) and multiple users are involved. The proposed solution is based on the extension of the categories-based filtering method using interval type 2 fuzzy sets for representing each category and the user preferences. Experimental results, that illustrate the feasibility of this approach, are provided.
Year
DOI
Venue
2010
10.1109/FUZZY.2010.5584813
FUZZ-IEEE
Keywords
Field
DocType
data structures,fuzzy set theory,information filtering,information filtering,information representation,interval type 2 fuzzy sets
Data mining,Data structure,Defuzzification,Computer science,Fuzzy set operations,Fuzzy set,Artificial intelligence,Cluster analysis,Fuzzy number,Type-2 fuzzy sets and systems,Membership function,Machine learning
Conference
ISSN
Citations 
PageRank 
1098-7584
0
0.34
References 
Authors
5
4
Name
Order
Citations
PageRank
Francisco P. Romero123527.46
Jesús Serrano-Guerrero2599.31
José Angel Olivas36512.87
Andrés Soto4194.36