Fuzzy Classification on Relational Databases

Abstract

In practice, information systems are based on very large data collections mostly stored in relational databases. As a result of information overload, it has become increasingly difficult to analyze huge amounts of data and to generate appropriate management decisions. Furthermore, data are often imprecise because they do not accurately represent the world or because they are themselves imperfect. For these reasons, a context model with fuzzy classes is proposed to extend relational database systems. More precisely, fuzzy classes and linguistic variables and terms, together with appropriate membership functions, are added to the database schema. The fuzzy classification query language (fCQL) allows the user to formulate unsharp queries that are then transformed into appropriate SQL statements using the fCQL toolkit so that no migration of the raw data is needed. In addition to the context model with fuzzy classes, fCQL and its implementation are presented here, illustrated by concrete examples.

Towards Fuzzy Analytics for Digital Video Advertising Campaign Effectiveness and Customer Experience

“…One of the fundamentals of marketing science is that customer behavior cannot be claimed to be well understood until it can be detailed into quantitative terms [21]. Fuzzy logic set effectively handles vague, inexact, stochastic input variables, and treats the dynamic nature of such variables.…”

Inductive Fuzzy Classification in Marketing Analytics

“…Fuzzy association analysis computes association rules between fuzzy restrictions on variables. Fuzzy classification partitions sharp data into fuzzy sets according to a classification predicate (Meier, Schindler, & Werro, 2008). If this predicate is inferred by induction, the process is called inductive fuzzy classification, or IFC (Kaufmann & Meier, 2009).…”

“…It has been discussed, for example, by Zimmermann (1997), Del Amo et al (1999, and Meier et al (2008). A fuzzy classification is achieved by a membership function, : ⟶ [0,1], that indicates the degree to which an individual is a member of a fuzzy class, , given the corresponding fuzzy propositional function, .…”

“…In data analysis, or "the search for structure in data" (Zimmermann H. J., 1997), fuzzy classification is a method for gradation in data consolidation, as presented by Meier, Schindler, andWerro (2008) andDel Amo, Montero, andCutello (1999). The application of fuzzy classification to marketing analytics (Spais & Veloutsou, 2005) has the advantage of precisiation (sic; Zadeh, 2008) of fuzzy concepts in the context of decision support for direct customer contact, as proposed by Werro (2008).…”

“…1 1. .1 1 R Re es se ea ar rc ch h Q Qu ue es st ti io on ns s Werro (2008) and Meier et al (2008) proposed the application of Fuzzy classification to customer relationship management (CRM). A suggestion for further research by Werro (2008), namely the integration of data mining techniques into fuzzy classification software, has inspired the present thesis.…”