Linguistic quantifiers extend the set of quantifiers of classical logic. They can be either crisp (such as all, at least 1, at least k, half) or fuzzy quantifiers (such as most, several, some, approximately k). Formally, Zadeh (1983) first defined fuzzy quantifiers as fuzzy subsets and identified two types of quantifiers: absolute and relative. Absolute quantifiers, such as about 7, almost 6, and so forth are defined as fuzzy sets with membership function on a subset of positive integers. Relative quantifiers are defined as fuzzy sets with membership function defined on [0,1].
Published in Chapter:
Customizable Flexible Querying in Classical Relational Databases
Bordogna Bordogna (CNR IDPA, Italy) and Guiseppe Psaila (University of Bergamo, Italy)
Copyright: © 2008
|Pages: 27
DOI: 10.4018/978-1-59904-853-6.ch008
Abstract
In this chapter, we present the Soft-SQL project whose goal is to define a rich extension of SQL aimed at effectively exploiting flexibility offered by fuzzy sets theory to solve practical issues when querying classic relational databases. The Soft-SQL language is based on previous approaches that introduced soft conditions on tuples in the classical relational database model. We retain the main features of these approaches and focus on the need to provide tools allowing users to directly specify the context dependent semantics of soft conditions. To this end, Soft-SQL provides a command (named CREATE TERM-SET) to define the semantics of linguistic values with respect to a context represented by a linguistic variable (Zadeh, 1975); the SELECT command is extended in order to support soft predicates based on the user defined term sets, the semantics of grouping and aggregation can be modified, and finally, the clauses in the SELECT command can be combined effectively.