Abstract
In recent years there has been a growing interest in the combination of rules and ontologies. Notably, many works have focused on the theoretical aspects of such integration, sometimes leading to concrete solutions. However, solutions proposed so far typically reason upon crisp concepts, while concrete domains require also fuzzy expressiveness.
In this work we combine mature technologies, namely the Drools business rule management system, the Pellet OWL Reasoner and the FuzzyDL system, to provide a unified framework for supporting fuzzy reasoning. After extending the Drools framework (language and engine) to support uncertainty reasoning upon rules, we have integrated it with custom operators that (i) exploit Pellet to perform ontological reasoning, and (ii) exploit FuzzyDL to support fuzzy ontological reasoning.
As a case study, we consider a decision-support system for the tourism domain, where ontologies are used to formally describe package tours, and rules are exploited to evaluate the consistency of such packages.
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Bragaglia, S., Chesani, F., Ciampolini, A., Mello, P., Montali, M., Sottara, D. (2010). An Hybrid Architecture Integrating Forward Rules with Fuzzy Ontological Reasoning. In: Graña Romay, M., Corchado, E., Garcia Sebastian, M.T. (eds) Hybrid Artificial Intelligence Systems. HAIS 2010. Lecture Notes in Computer Science(), vol 6076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13769-3_53
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DOI: https://doi.org/10.1007/978-3-642-13769-3_53
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