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Fuzz-TIME: an intelligent system for managing fuzzy temporal information

Aymen Gammoudi (Institut Superieur De Gestion De Tunis, LARODEC, Tunis, Tunisia)
Allel Hadjali (Laboratoire d’Informatique et d’Automatique pour les Systèmes, École nationale supérieure de mécanique et d’aérotechnique, Chasseneuil-du-Poitou, France)
Boutheina Ben Yaghlane (IHECT, University of Carthage, Tunis, Tunisia)

International Journal of Intelligent Computing and Cybernetics

ISSN: 1756-378X

Article publication date: 12 June 2017




Time modeling is a crucial feature in many application domains. However, temporal information often is not crisp, but is subjective and fuzzy. The purpose of this paper is to address the issue related to the modeling and handling of imperfection inherent to both temporal relations and intervals.


On the one hand, fuzzy extensions of Allen temporal relations are investigated and, on the other hand, extended temporal relations to define the positions of two fuzzy time intervals are introduced. Then, a database system, called Fuzzy Temporal Information Management and Exploitation (Fuzz-TIME), is developed for the purpose of processing fuzzy temporal queries.


To evaluate the proposal, the authors have implemented a Fuzz-TIME system and created a fuzzy historical database for the querying purpose. Some demonstrative scenarios from history domain are proposed and discussed.

Research limitations/implications

The authors have conducted some experiments on archaeological data to show the effectiveness of the Fuzz-TIME system. However, thorough experiments on large-scale databases are highly desirable to show the behavior of the tool with respect to the performance and time execution criteria.

Practical implications

The tool developed (Fuzz-TIME) can have many practical applications where time information has to be dealt with. In particular, in several real-world applications like history, medicine, criminal and financial domains, where time is often perceived or expressed in an imprecise/fuzzy manner.

Social implications

The social implications of this work can be expected, more particularly, in two domains: in the museum to manage, exploit and analysis the piece of information related to archives and historic data; and in the hospitals/medical organizations to deal with time information inherent to data about patients and diseases.


This paper presents the design and characterization of a novel and intelligent database system to process and manage the imperfection inherent to both temporal relations and intervals.



Gammoudi, A., Hadjali, A. and Ben Yaghlane, B. (2017), "Fuzz-TIME: an intelligent system for managing fuzzy temporal information", International Journal of Intelligent Computing and Cybernetics, Vol. 10 No. 2, pp. 200-222.



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Copyright © 2017, Emerald Publishing Limited

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