Dissertação
Modelo para identificação de contexto social através da inferência de interações sociais
Autor
Souza, Isadora Vasconcellos e
Institución
Resumen
Context-aware Computing is characterized by the development of devices capable of making
decisions, offering services and answers based on the user’s current context. It is
formed by different types of context, among them there is the social context. The main factor
of a social context is information about social relations. These relationships are formed
by a set of social interactions. Therefore, in this work we suggest the SocialCount, a model
of inference of social interactions face to face for the identification of a social context. The
challenge of the area is the use of abstract concepts (social interaction, social relation, social
context) in computational means. For the inference of social interactions we use a set
of approaches, the differential in relation to related works is the speaker recognition. The
identification of the social context is performed based on three factors: number of users
in the group, interactions between users and the main type of relationship present in the
group. In the experiment performed, the set of approaches used by SocialCount inferred
enough interactions to achieve an accuracy of 86% in the classification of relationships.
With respect to the identification of the social context, the context identified by SocialCount
obtained two factors (number of users in the group and interactions between users) equivalent
to the context recognized by the validator method. Thus, the model was able to achieve
the proposed goal of adequately inferring face-to-face social interactions made by the user,
identifying their social context.
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