REASONING ON THE SEMANTIC WEB FOR ADAPTIVE HYPERMEDIA
Keywords:
Semantic Web, Adaptive Systems, Reasoning, Ontologies, Standard Metadata, OWL, SWRLAbstract
So far, ontologies have been widely used to convey knowledge across the Semantic Web. Complementing web ontologies with Horn-like rules to assert relations among ontology individuals and properties is part of the ongoing implementation of the Semantic Web. Intelligent Web Adaptive Hypermedia Systems (AHS) are the next generation for adaptive hypermedia on the web. We present a web-based intelligent AHS for e-learning that configures on the fly complex learning objects tailored to the user profile. This automatic configuration is entirely accomplished by reasoning over a hybrid Knowledge Base (KB) composed of ontologies, and Horn-like rules defined on top of ontologies concepts. Interoperability on the semantic level is achieved by using an application profile of standard vocabularies, standard languages for the representation of ontologies and rules, and a standard interface for reasoning functionality.
Downloads
References
P. Brusilovsky, Methods and techniques of adaptive hypermedia. User Modeling and User-Adapted
Interaction, 6 (2-3), 87-129, 1996.
S. Bechhofer, F. van Harmelen, J. Hendler, I. Horrocks, D. McGuinness, P. Patel-Schneider and
L. Stein, OWL Web Ontology Language Reference. W3C Recommendation, 2004.
F. Baader, D. Calvanese, D. McGuinness, D. Nardi, and P. F. Patel-Schneider editors, The Description
Logic Handbook: Theory, Implementation and Applications. Cambridge University Press,
I. Horrocks, P. F. Patel-Schneider, S. Bechhofer, and D. Tsarkov, Owl rules: A proposal and
prototype implementation. Conditionally accepted for publication. Journal ofWeb Semantics, 2005.
R. Brachman, V. Gilbert and H. Levesque, An Essential Hybrid Reasoning System: Knowledge
and Symbol Level Accounts of KRYPTON. IJCAI 1985: 532-539.
B. Nebel, and K. vonLuck, Hybrid Reasoning in BACK. In Methodologies for Intelligent Systems,
Volume 3, eds. Z. W. Ras and L. Saitta, 260-269. New York: North-Holland, 1988.
A. Borgida, R. Brachman, D. McGuinness, and L. Resnick, CLASSIC: A structural data model
for objects. In Proc. Of the ACM SIGMOD Int. Conf. on Management of Data, pages 59-67, 1989.
A. Levy and M. Rousset, Combining Horn rules and description logics in CARIN. Artificial Intelligence,
(1-2):165-209, 1998.
I. Horrocks, P. Patel-Schneider, H. Boley, S. Tabets, B. Grosof, M. Dean, SWRL: A Semantic
Web Rule Language Combining OWL and RuleML W3C Member Submission 21 May 2004.
G. Antoniou, C. Damasio, B. Grosof, I. Horrocks, M. Kifer, J. Maluszynski, and P. Patel-Schneider,
Combining rules and ontologies. A survey. http://rewerse.net/deliverables/m12/i3-d3.pdf, 2005.
REWERSE Deliverables, No. I3-D3, February 2005.
R. Rosati. On the decidability and complexity of integrating ontologies and rules. Journal of Web
Semantics, 3, 2005.
V. Haarslev, R. Moller, RACER User’s Guide and Reference Manual. Version 1.7.7. 2003.
I. Horrocks, The FaCT system. In Harrie de Swart, editor, Proc. Of the 2nd Int. Conf. on Analytic
Tableaux and Related Methods (TABLEAUX’98), volume 1397 of Lecture Notes in Artificial
Intelligence, pages 307-312. Springer, 1998.
Jess Rule Engine: http://herzberg.ca.sandia.gov/jess/
S. Bechhofer, R. Moller, and P. Crowther, The DIG Description Logic Interface. In Proc. of
International Workshop on Description Logics (DL2003), Rome, Italy, 2003.
L. Silva-Mu˜noz, J. Palazzo, Adaptive Web-Based Courseware Development Using Metadata Standards
and Ontologies. The 16th International Conf. on Advanced Information Systems Engineering
- CAISE , volume 3084 of Lecture Notes in Computer Science, pages 414-428. Springer, 2004.
E. Duval, W. Hodgins, S. Sutton, S. Weibel, Metadata Principles and Practicalities. D-Lib Magazine
(4), 2002.
R. Heery, M. Patel, Application profiles: mixing and matching metadata schemas. September 2000,
ARIADNE Issue 25.
P. Brusilovsky, Developing Adaptive Educational Hypermedia Systems: ¿From Design Models to
Authoring Tools. in T. Murray, S. Blessing and S. Ainsworth (Eds.), In Press.
XQuery: http://www.w3.org/TR/xquery/
XPath: http://www.w3.org/TR/xpath/
P. V. Biron and A. Malhotra. XML schema part 2: Datatypes. W3C Recommendation,May 2001.
http://www.w3.org/TR/xmlschema-2/.
M. Nilsson, IEEE Learning Object Metadata RDF binding. May 2001.
http://kmr.nada.kth.se/el/ims/metadata.html.
Learning Technology Standards Committee of the IEEE. Draft Standard for Learning Object
Metadata (LOM) IEEE 1484.12.1-2002.
R. Riding, S. Rayner, Cognitive Style and Learning Strategies. London: David Fulton Publishers,
M. Souto, M. Nicolao, R. Viccari, J. Palazzo, R. Verdin, K. Beschoren, M. Madeira, R. Zanella,
Web Adaptive Training System Based on Cognitive Student Style. IFIPWorld Computer Congress,
th Edition, August 25-30, 2002, Montreal, Canada.
P. Patel-Schneider I. and Horrocks, 2006. Position paper: a comparison of two modelling paradigms
in the Semantic Web. In Proceedings of the 15th international Conference on World Wide Web
(Edinburgh, Scotland, May 23 - 26, 2006). WWW ’06. ACM Press, New York, NY, 3-12. DOI=
http://doi.acm.org/10.1145/1135777.1135784.
L. Silva-Mu˜noz, J. Palazzo, Applying Semantic Web Technologies to Improve Personalization and
Achieve Interoperability between Educational Adaptive Hypermedia Systems. International Workshop
on Applications of Semantic Web Technologies for Adaptive Educational Hypermedia. - SWEL’
, in conjunction with the International Conference on Adaptive Hypermedia and Adaptive
Web-Based Systems, August 23-26, 2004, Eindhoven, The Netherlands.
Dublin Core Metadata Element Set, Version 1.1: Reference Description. Available at
