Modelling and Representation of Uncertain Temporal Information

Chountas, Panagiotis; Petrounias, Ilias

doi:10.1007/s007660070006

Cited by 9 publications

(7 citation statements)

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“…In an information system, temporal information is usually related to facts or events [7]. In light of this, a classification of temporal information can be considered, in which the following types of temporal information may be found:…”

Section: Types Of Imperfections In Temporal Modellingmentioning

confidence: 99%

“…Some proposals [47], [10], [55], [7] conclude that the best representation for incomplete temporal knowledge is therefore based on time intervals, even if they refer to a fact that happen at a time point. This means that, as Allen proposed in [1], the primitive units (the chronons) in a time domain, used in an information system should be intervals.…”

Section: Representation Of Imperfect Informationmentioning

confidence: 99%

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Flexible Approaches in Data, Information and Knowledge Management

2014

Studies in Computational Intelligence

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Section: Types Of Imperfections In Temporal Modellingmentioning

confidence: 99%

Section: Representation Of Imperfect Informationmentioning

confidence: 99%

Flexible Approaches in Data, Information and Knowledge Management

2014

Studies in Computational Intelligence

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“…The information about fuzzy numbers may depend on different factors, in particular, on imprecision and certainty (Chountas and Petrounias, 2000). We focus on general types of information related only to these two factors.…”

Section: Iceis 2009 -International Conference On Enterprise Informatimentioning

confidence: 99%

Towards a Unified Domain for Fuzzy Temporal Databases

Garrido¹,

Marín

Pons³

2009

Proceedings of the 11th International Conference on Enterprise Information

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Temporal Databases (TDB) have as a primary aim to offer a common framework to those DB applications that need to store or handle temporal data of different nature or source, since they allow to unify the concept of time from the point of view of its meaning, its representation and its manipulation. At first sight, it may seem that incorporation of time to a DB is a direct and even simple task, but, on the contrary, it is a quite complex aim because time may be provided by different sources, with different granularities and meaning. The situation gets more complex when the time specification is not made in precise but in fuzzy terms, where together with the inherent problems of the time domain, we have to consider the imprecision factor. To deal with this problem, the first task to perform is to unify as much as possible the representation of time in order to be able to define the range and the semantics of the necessary operators to handle data of this type.

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“…For example, patient DBS may need to model patients' medical history by containing data representing the time intervals during which the patients suffered from certain diseases or data representing the instants when the patients took medication. Because time intervals in DBS are studied more exhaustively in literature [1], [2], [5], [8], [12], [14], [15], [16], [17] than instants in DBS [7], [8] and because an instant can be seen (and modeled) as a time interval, the work presented in this paper only considers time intervals in DBS.…”

Section: Introductionmentioning

confidence: 99%

Combining Uncertainty and Vagueness in Time Intervals

Billiet

Tré

2015

Advances in Intelligent Systems and Computing

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Database systems contain data representing properties of real-life objects or concepts. Many of these data represent time indications and such time indications are often subject to imperfections. Although several existing proposals deal with the modeling of uncertainty or vagueness in time indications in database systems, only a few of them summarily examine the interpretation and semantics of such imperfections. The work presented in this paper starts at a more thorough examination of the semantics and modeling of uncertainty or vagueness in time intervals in database systems and presents methods to model combinations of uncertainty and vagueness in time intervals in database systems, based on examinations of their requisite interpretations.

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Modelling and Representation of Uncertain Temporal Information

Cited by 9 publications

References 0 publications

Flexible Approaches in Data, Information and Knowledge Management

Flexible Approaches in Data, Information and Knowledge Management

Towards a Unified Domain for Fuzzy Temporal Databases

Combining Uncertainty and Vagueness in Time Intervals

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