Generic Multimodal Ontologies for Human-Agent Interaction
Watching the evolution of the Semantic Web (SW) from its inception to these days we can easily observe that the main task the developers face while building it is to encode the human knowledge into ontologies and the human reasoning into dedicated reasoning engines. Now, the SW needs to have efficient mechanisms to access information by both humans and artificial agents. The most important tools in this context are ontologies. The last years have been dedicated to solving the infrastructure problems related to ontologies: ontology management, ontology matching, ontology adoption, but as time goes by and these problems are better understood the research interests in this area will surely shift towards the way in which agents will use them to communicate between them and with humans. Despite the fact that interface agents could be bilingual, it would be more efficient, safe and swift that they should use the same language to communicate with humans and with their peers. Since anthropocentric systems entail nowadays multimodal interfaces, it seems suitable to build multimodal ontologies. Generic ontologies are needed when dealing with uncertainty. Multimodal ontologies should be designed taking into account our way of thinking (mind maps, visual thinking, feedback, logic, emotions, etc.) and also the processes in which they would be involved (multimodal fusion and integration, error reduction, natural language processing, multimodal fission, etc.). By doing this it would be easier for us (and also fun) to use ontologies, but in the same time the communication with agents (and also agent to agent talk) would be enhanced. This is just one of our conclusions related to why building generic multimodal ontologies is very important for future semantic web applications.
multimodal ontology human-agent interaction semantic web ontology matching interface agents