Authors:
Marcelo Loor
1
and
Guy De Tré
2
Affiliations:
1
Ghent University and ESPOL University, Belgium
;
2
Ghent University, Belgium
Keyword(s):
Experience-Based Evaluations, Similarity Measures, Intuitionistic Fuzzy Sets.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Fuzzy Information Processing, Fusion, Text Mining
;
Fuzzy Information Retrieval and Data Mining
;
Fuzzy Systems
;
Pattern Recognition: Fuzzy Clustering and Classifiers
;
Soft Computing
;
Soft Computing and Intelligent Agents
Abstract:
Which similarity measures can be used to compare two Atanassov’s intuitionistic fuzzy sets (IFSs) that respectively
represent two experience-based evaluation sets? To find an answer to this question, several similarity
measures were tested in comparisons between pairs of IFSs that result from simulations of different
experience-based evaluation processes. In such a simulation, a support vector learning algorithm was used to
learn how a human editor categorizes newswire stories under a specific scenario and, then, the resulting knowledge
was used to evaluate the level to which other newswire stories fit into each of the learned categories. This
paper presents our findings about how each of the chosen similarity measures reflected the perceived similarity
among the simulated experience-based evaluation sets.