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Title: A Rule-based Object-Oriented OWL Reasoner
Author(s): G. Meditskos, N. Bassiliades.
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Appeared in: IEEE Transactions on Knowledge and Data Engineering, IEEE, vol. 20, no. 3, pp. 397-410, 2008.
Abstract: In this paper we describe O-DEVICE, a memory-based knowledge base system for reasoning and querying OWL ontologies by implementing RDF/OWL entailments in the form of production rules in order to apply the formal semantics of the language. Our approach is based on a transformation procedure of OWL ontologies into an Object-Oriented schema and the application of inference production rules over the generated objects in order to implement the various semantics of OWL. In order to enhance the performance of the system, we introduce a dynamic approach of generating production rules for ABOX reasoning and an incremental approach of loading ontologies. O-DEVICE is built over the CLIPS production rule system, using the object-oriented language COOL to model and handle ontology concepts and RDF resources. One of the contributions of our work is that we enable a well-known and efficient production rule system to handle OWL ontologies. We argue that although native OWL rule reasoners may process ontology information faster, they lack some of the key features that rule systems offer, such as the efficient manipulation of the information through complex rule programs. We present a comparison of our system with other OWL reasoners, showing that O-DEVICE can constitute a practical rule environment for ontology manipulation.
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1 Smart, Paul R (2007) Rule-Based Intelligence on the Semantic Web: Implications for Military Capabilities, Technical Report, University of Southampton, Faculty of Physical and Applied Science, Electronics and Computer Science, Web & Internet Science, http://eprints.soton.ac.uk/id/eprint/264912.
2 Qu, Q., Qiu, J., Sun, C., Wang, Y., “Graph-based knowledge representation model and pattern retrieval”, (2008) Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008, 5, art. no. 4666584, pp. 541-545.
3 Nami, M. R. 2008. “A comparison of object-oriented languages in software engineering”, SIGSOFT Softw. Eng. Notes, 33(4), Jul. 2008, pp. 1-5.
4 Smart, P. R., Russell, A., Liang, S., Shadbolt, N. R., Booth, C., Briscombe, N. and Rankin, A. (2009) Using Semantic Technologies to Improve Information Exploitation in Military and Civilian Application Contexts. In: Knowledge Systems for Coalition Operations, 31st March-1st April 2009, Southampton, UK.
5 Shazzad Hosain and Hasan Jamil, “Empowering OWL with Overriding Inheritance, Conflict Resolution and Non-monotonic Reasoning”, Proceedings of the AAAI 2009 Spring Symposium on Social Semantic Web: Where Web 2.0 meets Web 3.0, 2009.
6 P.J. McBrien, N. Rizopoulos, and A.C. Smith, “SQOWL: Performing OWL-DL type inference in SQL”, AutoMed Technical Report No 37, 2009.
7 Wei Tai, Rob Brennan, John Keeney, Declan O'Sullivan, "An Automatically Composable OWL Reasoner for Resource Constrained Devices," International Conference on Semantic Computing, pp. 495-502, 2009 IEEE International Conference on Semantic Computing, 2009.
8 A. Marginean, "Blending rules and ontology in argumentation", Proc. of the 31st Int. Conf. on Information Technology Interfaces (ITI'09), pp. 493 - 498, 2009.
9 Jose Luis Lopez Cuadrado, "Definicion de un modelo de representacion del conocimiento para procesos de estimacion de presupuestos", PhD thesis, Departamento de Informatica, Universidad Carlos III de Madrid, Spain, Dec 2009.
10 MD. Shazzad Hosain, “An Algebraic Foundation For Automatic Semantic Data Integration On The Hidden Web”, Phd Dissertation, Graduate School of Wayne State University, Detroit, Michigan, 2010.
11 Hudson, D. L. 2010. Knowledge-Based Systems. Wiley Encyclopedia of Electrical and Electronics Engineering. 1–9.
12 Chen, P.-C., Airy, G., Mitra, P., Yen, J., “Extending legacy agent knowledge base systems with semantic Web compatibilities”, (2010) ICEIS 2010 - Proceedings of the 12th International Conference on Enterprise Information Systems, 4 SAIC, pp. 131-134.
13 Fu Zhang, Z. M. Ma, Xing Wang, Yu Wang,Formal approach and automated tool for constructing ontology from object-oriented database model, Proceedings of the 19th ACM Conference on Information and Knowledge Management (CIKM 2010), pp. 1329-1332, 2010.
14 Sottara, D., S. Bragaglia, F. Chesani, and P. Mello, "A Rule-Based Implementation of Fuzzy Tableau Reasoning", Proceedings of the 4th International Web Rule Symposium: Research Based and Industry Focused (RuleML 2010), October 21-23, 2010, Washington, DC, USA.
15 Fu Zhang, Z. M. Ma, Gaofeng Fan, Xing Wang, “Automatic Fuzzy Semantic Web Ontology Learning from Fuzzy Object-Oriented Database Model”, Proc. 21st Int. Database and Expert Systems Applications Conference (DEXA 2010), Bilbao, Spain, Part I, LNCS 6261, Springer, 2010, pp. 16-30.
16 Christian Seitz, Steffen Lamparter, Thorsten Scholer, and Michael Pirker, “Embedded Rule-based Reasoning for Digital Product Memories”, AAAI Spring Symposium Series, pp. 98-103, 2010.
17 A. Garcia-Crespo, B. Ruiz-Mezcua, J.L. Lopez-Cuadrado, J.M. Gomez-Berbis, Conceptual model for semantic representation of industrial manufacturing processes, Computers in Industry, 61(7), Sep 2010, pp. 595-612.
18 Shen Furao, Akihito Sudo, Osamu Hasegawa, “An online incremental learning pattern-based reasoning system”, Neural Networks, Volume 23, Issue 1, January 2010, pp. 135-143.
19 Peter McBrien, Nikos Rizopoulos and Andrew Smith, "SQOWL: Type Inference in an RDBMS", 29th International Conference on Conceptual Modeling Vancouver, BC, Canada, 2010
20 Jaroslaw Bak, Maciej Falkowski and Czeslaw Jedrzejek, "The SDL Library: Querying a Relational Database with an Ontology, Rules and the Jess Engine", 5th International Web Rule Symposium: Research-Based and Industry-Focused November 3rd-5th, 2011, Westin Diplomat, Ft. Lauderdale, Florida
21 R. B. Mishra and Sandeep Kumar, "Semantic web reasoners and languages", Artificial Intelligence Review, 35(4), pp. 339-368, 2011.
22 Bry Francois, Furche Tim, Ley Clemens, Marnette Bruno, Linse Benedikt, Schaffert Sebastian, “Datalog Relaunched: Simulation Unification and Value Invention, Proceedings of the Datalog 2.0 Workshop, 2011.
23 Tai, Wei, Keeney, John, O’Sullivan, Declan, "COROR: A COmposable Rule-Entailment Owl Reasoner for Resource-Constrained Devices", Rule-Based Reasoning, Programming, and Applications (RuleML-2011@Europe), LNCS 6826, Springer, pp. 212-226, 2011.
24 Christian Seitz and Rene Schonfelder, “Rule-based OWL Reasoning for specific Embedded Devices”, 10th International Semantic Web Conference (ISWC-2011), Semantic Web in Use Track, October 23-27, 2011, Bonn, Germany, Volume 7032 LNCS, PART 2, 2011, pp. 237-252.
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26 Fu Zhang, Z.M. Ma, Li Yan, "Construction of ontologies from object-oriented database models", Integrated Computer-Aided Engineering, 18(4), pp. 327-347, IOS Press, 2011.
27 D. Sottara, S. Bragaglia, D. Pulcini, P. Mello, D. Giunchi, L. Luccarini, "Ontologies, Rules, Workflow and Predictive Models: Knowledge Assets for an EDSS", International Environmental Modelling and Software Society (iEMSs) - International Congress on Environmental Modelling and Software, Leipzig, 1-5 July 2012.
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29 Chenrong Jing, Lin Yung, “The Recommendation of Diet for Chronic Diseases Based on Knapsack Problem and Domain Ontology”, International Journal of Advanced Information Technologies, 6(2), p.155-167, 2012.
30 Charalampos Doulaverakis, George Nikolaidis, Athanasios Kleontas and Ioannis Kompatsiaris, "GalenOWL: Ontology based drug recommendations discovery", Journal of Biomedical Semantics 2012, 3:14, doi:10.1186/2041-1480-3-14.
31 Depuru, S.S.S.R., Wang, L., Devabhaktuni, V., “A rule engine based classification algorithm for detection of illegal consumption of electricity”, 2012 North American Power Symposium, NAPS 2012, art. no. 6336359.
32 C. Doulaverakis, G. Nikolaidis, A. Kleontas and I. Kompatsiaris, "GalenOWL: Ontology based drug recommendations discovery", in Vaccine and Drug Ontology in the Study of Mechanism and Effect (VDOSME 2012), Workshop of the 3rd international Conference on Biomedical Ontology (ICBO 2012), July 21, 2012, Graz, Austria
33 Stefano Bragaglia, Paola Mello, Davide Sottara, “Towards an Interactive Personal Care System driven by Sensor Data”, Popularize Artificial Intelligence (PAI 2012), Proceedings of the AI*IA Workshop and Prize for Celebrating 100th Anniversary of Alan Turing's Birth Rome, Italy, June 15, 2012
34 McBrien, P., Rizopoulos, N., Smith, A.C. "Type inference methods and performance for data in an RDBMS", In Proceedings of the 4th International Workshop on Semantic Web Information Management (SWIM '12), pp. 1-8, ACM, New York, NY, USA, 2012
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38 Ma, Y., Yu, X., "An ontology based approach for disaster prediction", (2013) Journal of Theoretical and Applied Information Technology, 51 (3), pp. 447-453.
39 Dan Wu, “Ontology Integration with Non-Violation Check and Context Extraction”, Licentiate Thesis in Information and Communication Technology, KTH Royal Institute of Technology, School of Intormation and Communication Technology, Department of Software and Computer Systems, Stockholm, Sweden 2013.
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42 Rivero, C.; Hernández, I.; Ruiz, D.; Corchuelo, R.; , "Benchmarking Data Exchange Amongst Semantic-Web Ontologies," Knowledge and Data Engineering, IEEE Transactions on, 25(9), pp. 1997-2009, 2013.
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45 OVALLE, Demetrio A; SALAZAR, Oscar M y DUQUE, Néstor D. Modelo de Recomendación Personalizada en Cursos Virtuales basado en Computación Ubicua y Agentes Inteligentes. Inf. tecnol. [online]. 2014, vol.25, n.6, pp. 131-142. ISSN 0718-0764.
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47 Chen, R.-C., Lo, Y.-W., Jiang, H., “The application of topsis algorithm to diabetic diet recommendation”, (2015) ICIC Express Letters, Part B: Applications, 6 (4), pp. 1105-1111.


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