Contribution À L’amélioration Des Stratégies De L’entreprise En Utilisant Social Internet Des Objets

Résumé: The Internet of Things (IoT) integrates several technologies and envisions a variety of things or objects around us thatthrough unique addressing schemes and standard communication protocols. In addition, as time goes on, more and more smart objects will be connected. Therefore, countless advantage will be available for the enterprises. The Internet of Things allows companies tocapture data from various sources in real-time and become more responsive to emerging trends and threats.Besides, accurate forecasts and new forms of data analysis tools allow the organization to predict future patterns and behaviors. The IoT recommender system provides recommendations of IoT services appropriateto the users' preferences based on the historical utilization and evaluation. Therefore,when the preferences of some users change, the company can benefit from theupdated recommendations to predict users ‘needs and requirements. So, adopting IoTrecommender systems enables enterprises to improve their strategies. Indeed, IoT has specific characteristics which may make some applications suffer from some shortcomings and may become incapable of achieving efficient tasks in the IoT. However, recently the idea that the convergence between the "Internet of Things" and the "Social Networks" paradigms has become possible.The a "Social Internet of Things" (SIoT) is a promising paradigm that would carry many desirable implications, implications, such as relationships and trustworthiness management,into a future world populated by intelligent objects. In this thesis, we proposed a hybrid recommendation approach using the available IoT data provided by different devices efficiently to feed the services by needed data using the findability/ service discovery as well as the service, in which, objects that belong to friends are allowed to collaborate to accomplish the IoT service on the behalf of the current user.

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