Um Modelo para Gerenciamento de Perfis de Entidades Através de Inferência em Trilhas

Abstract

Context-aware and ubiquitous systems have the challenge of implicitly collect relevant information about entities, and use this information to understand and predict their behaviour. This allows the applications to adapt themselves to the entities, thus avoiding to overflow them with inquires and information. The analysis of trails, the context-aware history of actions, can further improve the relevance of information. This dissertation proposes a model that allows applications to register entites’ actions in trails and infer profile information from these trails, using semantic interoperability and thus allowing different applications to share information and infer a unified profile. A prototype was developed for the evaluation of the model, and it was integrated with two different softwares. It was verified that was possible to enrich the profile generation of applications through the integration with the modelo. The contributions of this model are the use of trails for extracting profiles, the generation of dynamic profiles, the capability of managing dynamic inference rules for profile generation and the semantic interoperabilty of the model.