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Conference Papers Year : 2022

Typology of Data Inputs Imperfection in Collective Memory Model

Abstract

Handling imperfect data inputs in applications for collective and individual memory is a crucial issue in shaping an updated and unprecedented view of it. In the literature, several typologies of data imperfections are proposed. However, these typologies cannot be applied to this context due to its particular specificities. In this paper, we propose a typology of imperfection for data entered by users in the applications for collective and individual memory. It includes nine direct imperfections types and four indirect ones. The direct ones are generated directly from the data inputs e.g., uncertainty and imprecision. The indirect imperfection types are generated from the direct ones, e.g., inconsistency is generated from uncertainty. We finish by representing an example of imprecise temporal data in the Collective Memo Onto (CMO) ontology.
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Dates and versions

hal-03687139 , version 1 (03-06-2022)

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Haithem Kharfia, Fatma Ghorbel, Bilel Gargouri. Typology of Data Inputs Imperfection in Collective Memory Model. 21st International Conference on Intelligent Systems Design and Applications ISDA 2021, Dec 2021, En ligne, United States. pp.1198-1206, ⟨10.1007/978-3-030-96308-8_111⟩. ⟨hal-03687139⟩
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