Specifying Ontologies in a Social Networking Images’ Sample Obtained with a Multiagent System

Abstract

In the present research, there are described some promising initial results of induced ontologies from vocabularies of labels in Metroflog, which were selected using Multi agent Systems utilizing a model based on suppositions. We describe the utility of the ontology of aspects as a supplement to a system that marks with labelling and we present our model and results. We propose a probabilistic reviewed model, using seed ontologies to induce ontology of aspects, and we describe how the model can integrate inside of the community’s logistics of labelling. An innovation of our research is having been able to improve the characterization of a group of labels associated with different images and how our multi-agent system uses a Belief–Desire-Intention (BDI) architecture is much more suitable to expand our context-based vocabulary and better describe the details fine of each image and what they really represent for a social group.