Fuzzy quantification for linguistic data analysis and data mining

TL;DR

This paper reviews fuzzy quantification, a fuzzy logic subfield, highlighting its applications in linguistic data analysis and data mining, emphasizing its ability to model natural language expressions mathematically.

Contribution

It provides a comprehensive overview of fuzzy quantifiers' applications in data analytics and proposes ideas for new application contexts.

Findings

Fuzzy quantifiers effectively model linguistic expressions mathematically.

Successful applications in fuzzy control, databases, and information retrieval.

Potential for new data mining applications.

Abstract

Fuzzy quantification is a subtopic of fuzzy logic which deals with the modelling of the quantified expressions we can find in natural language. Fuzzy quantifiers have been successfully applied in several fields like fuzzy, control, fuzzy databases, information retrieval, natural language generation, etc. Their ability to model and evaluate linguistic expressions in a mathematical way, makes fuzzy quantifiers very powerful for data analytics and data mining applications. In this paper we will give a general overview of the main applications of fuzzy quantifiers in this field as well as some ideas to use them in new application contexts.