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

Sabrine Jandoubi, Afef Bahri, Nadia Yacoubi Ayadi, Salem Chakhar, Ashraf Wasfi Labib

Research output: Contribution to journalArticlepeer-review

94 Downloads (Pure)

Abstract

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 minimize the space required to store imperfect information, and access efficiently and effectively these databases.
Original languageEnglish
Pages (from-to)152-169
Number of pages18
JournalJournal of Decision Systems
Volume26
Issue number2
Early online date7 Nov 2016
DOIs
Publication statusPublished - 8 Feb 2017

Keywords

  • Large data-sets
  • imperfect information
  • uncertainty
  • imprecision
  • fuzziness
  • incomplete data
  • fuzzy attributes
  • fuzzy database
  • mapping rule

Fingerprint

Dive into the research topics of 'Modelling, representation and implementation of imperfect information for an enhanced exploration of large databases'. Together they form a unique fingerprint.

Cite this