Hybrid knowledge representation and reasoning
The goal is to define and realize hybrid approaches for integrating ontological, rule-based and fuzzy-like knowledge representation formalisms and reasoning techniques.From a methodological viewpoint, we are investigating the integration of such formalisms and reasoning techniques in accordance with two diverse approaches: tight and loose integration.
The tight integration involves (i) the definition of a coherent theory enough complex to support all the selected representation formalisms and reasoning styles; and (ii) the development of a single reasoner able to understand a unique language and semantics, and to manage the expressed knowledge accordingly.
The loose integration involves the delegation of each reasoning task to different sub-systems, each of them being characterized by its peculiarity in terms of expressiveness and reasoning capabilities. A unifying framework is foreseen on the top of these sub-systems, which is equipped with a meta-level knowledge, concerning the different reasoning tasks as well as their processing order, and when and under what conditions they have to be performed.
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- S. Colantonio, G. De Pietro, M. Esposito, A. Machì, M. Martinelli, O. Salvetti. Decision Support for the Remote Management of Chronic Patients. In the 2nd International ICST Conference on Wireless Mobile Communication and Healthcare MobiHealth 2011, 5-7 October 2011, Kos Island, Greece.
- S. Colantonio, G. De Pietro, M. Esposito, A. Machì, M. Martinelli, O. Salvetti. Knowledge Based Decision Support For The Management Of Chronic Patients. In the International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 26-29 October 2011, Paris, France.
- S. Colantonio, G. De Pietro, M. Esposito, M. Martinelli, O. Salvetti: A Knowledge Editing Service for Multisource Data Management in Remote Health Monitoring. IEEE Transactions on Information Technology in BioMedicine. Published online 27 August 2012. DOI 10.1109/TITB.2012.2215622.