Modelling, representation and implementation of imperfect information for an enhanced exploration of large databases

The rapid development of social networks, intelligent sensors, mobile solutions and Internet of things has led to the emergence of large data-sets. Efficiently and effectively exploring these data-sets is a challenging question, especially when the imperfectness of real-world needs to be taken into...

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Bibliographic Details
Published inJournal of decision systems Vol. 26; no. 2; pp. 152 - 169
Main Authors Jandoubi, Sabrine, Bahri, Afef, Yacoubi Ayadi, Nadia, Chakhar, Salem, Labib, Ashraf
Format Journal Article
LanguageEnglish
Published Taylor & Francis 03.04.2017
Subjects
fuzziness
fuzzy attributes
fuzzy database
imperfect information
imprecision
incomplete data
Large data-sets
mapping rule
uncertainty
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Summary:The rapid development of social networks, intelligent sensors, mobile solutions and Internet of things has led to the emergence of large data-sets. Efficiently and effectively exploring these data-sets is a challenging question, especially when the imperfectness of real-world needs to be taken into account. The objective of this paper is thus to propose several solutions for modelling, representing and implementing imperfect information within large fuzzy databases. More specifically, in this paper imperfect information is modelled through a series of generic fuzzy data types, uniformly represented by means of possibility distributions and implemented using the basic constructs of object databases. These solutions are particularly useful for exploring large fuzzy databases since they permit to minimise the space required to store imperfect information, and access efficiently and effectively these databases.
ISSN:1246-0125
2116-7052
DOI:10.1080/12460125.2017.1252232