Skip to Main content Skip to Navigation

Traitement de l’imperfection des données temporelles saisies par l’utilisateur : application aux logiciels destinés à des patients malades d’Alzheimer

Abstract : The need to deal with temporal data imperfection in the Semantic Web is increasing and, therefore, calls for a standard way of representing and reasoning about such data. This thesis presents a new vision aiming to provide solutions for different types of imperfections affecting temporal data, which we first define in a typology that we propose. Our thesis includes several contributions. The first one consists in defining a typology of temporal data imperfection in which we elaborate the various imperfections that can af-fect temporal data. We classify them into direct imperfections and others that are indirect. Then, we move to dealing with these imperfections in ontology. We propose an approach to deal with imprecision by representing and reasoning about dates and time clocks and associ-ated qualitative relations in ontology with a crisp view. Therefore, we extend the 4D-Fluents approach for the representation and the Allen’s interval algebra for the reasoning. Then, we create an ontology based on our extensions called « CrispImpTimeOnto ». When dealing with uncertain temporal data in ontology and associated qualitative relations, we first pro-pose an approach in a certain environment. We calculate certainty degrees using Bayesian networks. We extend the 4D-Fluents approach to represent the handled data and extending Allen’s interval algebra for the reasoning part. Second, we propose an approach base on pos-sibility theory to calculate the necessity measures of the handled data and by extending the same approaches for representation and reasoning. Then, we conduct a small comparison between the two proposed approaches. We offer an ontology based on our extensions called “UncertTimeOnto”. Temporal data may, also, be affected by multiple types of imperfec-tions at the same time. Thus, we present a contribution which consists in dealing with simul-taneously uncertain and imprecise temporal data in ontology using possibility theory. We propose an ontology, named « UncertPossibTimeOnto », based on our extensions. We deal with the conflict of temporal data in ontology by using the evidential theory to calculate the belief masses of the handled data. We propose a semantic representation based on the ob-tained measures. We also extend Allen’s algebra to reason about conflicting temporal data. We propose an ontology, named « BeliefTimeOnto » based on our extensions. Based on the proposed ontologies in the previous chapters, we propose an ontology of temporal data im-perfection called « TemporalOntoImperfection » that encompasses all the treated imperfec-tions. Our contributions are implemented and evaluated within CAPTAIN MEMO, the memory prosthesis based on the PersonLink ontology, dedicated to Alzheimer’s patients. We integrate our temporal ontology « TemporalOntoImperfection» in the prosthesis and we evaluate our approaches dealing with the different types of imperfection. This assessment involves people with Alzheimer’s disease.
Document type :
Complete list of metadata
Contributor : ABES STAR :  Contact
Submitted on : Monday, May 23, 2022 - 8:21:25 AM
Last modification on : Friday, August 5, 2022 - 2:54:00 PM


Version validated by the jury (STAR)


  • HAL Id : tel-03675221, version 2



Nassira Achich. Traitement de l’imperfection des données temporelles saisies par l’utilisateur : application aux logiciels destinés à des patients malades d’Alzheimer. Ordinateur et société [cs.CY]. HESAM Université; Université de Sfax (Tunisie), 2021. Français. ⟨NNT : 2021HESAC024⟩. ⟨tel-03675221v2⟩



Record views


Files downloads