My mood, a multimedia and multilingual ontology driven MAS: Design and first experiments in the sentiment analysis domain

In this paper we introduce the architecture of a Multimedia and Multilingual Ontology Driven Multiagent System (My MOoD) for classifying documents consisting of audiovisual and textual elements, according to classes described in a domain ontology. My MOoD will integrate software components devoted to the analysis of images, videos, and sound, with the multilingual text classifier based on BabelNet presented in this paper. All the integrated components will be wrapped by agents and will perform their classification based on a common domain ontology, which is a parameter of the multiagent system. Wrapper agents will interact in order to share the classification of the document’s elements and agree on a coherent classification of the document as a whole, exploiting their background knowledge and reasoning capability to resolve ambiguities. Changing the ontology (and tuning or substituting the classifiers for dealing with the domain of interest) will allow the multiagent system to classify heterogeneous multimedia documents in whatever domain and for many different purposes. In the My MOoD instance discussed in this paper, the ontology (sentiHotel) describes the accommodation domain and the classification mines the sentiment of hotel reviews written in five different languages.