| Titre : | Apprentissage du contexte pour les systèmes predictifs | | Type de document : | projet fin études | | Auteurs : | TAHER Maryeme, Auteur | | Langues : | Anglais (eng) | | Catégories : | Internet des Objets et Services Mobiles ( IOSM )
| | Mots-clés : | Context-Aware Services, Context-Awareness, Machine Learning,
Context Prediction, Smart Parking, MLP. | | Index. décimale : | mast 70/18 | | Résumé : | Ubiquitous computing promotes the creation of intelligent environments based
on the user’s contextual knowledge to provide a context-aware service.
A new trend in this area of research takes into account the evolution of contextual
information over time in order to predict a context. As a result, the future context
allows the ubiquitous system to choose more effective strategies to achieve its goals
and allows for rapid adaptation to future situations. This raises our interest in
context prediction and its integration into the adaptation of context-aware services.
Machine learning is a new technology that can be used to predict a context.
In this work, we present a state of the art of approaches dedicated to the prediction
of the context. Next, we propose an approach of a context-aware predictive
system using machine learning to meet the requirements of ubiquitous computing
and the contextual services required according to the needs of the user and his
environment.
This approach, dubbed "MLP Context Prediction", is validated by the development
of a context-aware service "Smart Parking" using the "MLP" classification
algorithm.
|
Apprentissage du contexte pour les systèmes predictifs [projet fin études] / TAHER Maryeme, Auteur . - [s.d.]. Langues : Anglais ( eng) | Catégories : | Internet des Objets et Services Mobiles ( IOSM )
| | Mots-clés : | Context-Aware Services, Context-Awareness, Machine Learning,
Context Prediction, Smart Parking, MLP. | | Index. décimale : | mast 70/18 | | Résumé : | Ubiquitous computing promotes the creation of intelligent environments based
on the user’s contextual knowledge to provide a context-aware service.
A new trend in this area of research takes into account the evolution of contextual
information over time in order to predict a context. As a result, the future context
allows the ubiquitous system to choose more effective strategies to achieve its goals
and allows for rapid adaptation to future situations. This raises our interest in
context prediction and its integration into the adaptation of context-aware services.
Machine learning is a new technology that can be used to predict a context.
In this work, we present a state of the art of approaches dedicated to the prediction
of the context. Next, we propose an approach of a context-aware predictive
system using machine learning to meet the requirements of ubiquitous computing
and the contextual services required according to the needs of the user and his
environment.
This approach, dubbed "MLP Context Prediction", is validated by the development
of a context-aware service "Smart Parking" using the "MLP" classification
algorithm.
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