TY - GEN
T1 - An hybrid architecture integrating forward rules with fuzzy ontological reasoning
AU - Bragaglia, Stefano
AU - Chesani, Federico
AU - Ciampolini, Anna
AU - Mello, Paola
AU - Montali, Marco
AU - Sottara, Davide
PY - 2010/7/20
Y1 - 2010/7/20
N2 - 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.
AB - 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.
KW - Decision Support Systems
KW - Fuzzy Reasoning
KW - Rule-based Reasoning
KW - Rules Integration with Ontologies
KW - eTourism
UR - http://www.scopus.com/inward/record.url?scp=77954572683&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77954572683&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-13769-3_53
DO - 10.1007/978-3-642-13769-3_53
M3 - Conference contribution
AN - SCOPUS:77954572683
SN - 3642137687
SN - 9783642137686
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 438
EP - 445
BT - Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings
T2 - 5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010
Y2 - 23 June 2010 through 25 June 2010
ER -