Resources-Based Ontology Matching to Access Learning Resources

Authors: A. Elbyed

Abstract:

Nowadays, ontologies are used for achieving a common understanding within a user community and for sharing domain knowledge. However, the de-centralized nature of the web makes indeed inevitable that small communities will use their own ontologies to describe their data and to index their own resources. Certainly, accessing to resources from various ontologies created independently is an important challenge for answering end user queries. Ontology mapping is thus required for combining ontologies. However, mapping complete ontologies at run time is a computationally expensive task. This paper proposes a system in which mappings between concepts may be generated dynamically as the concepts are encountered during user queries. In this way, the interaction itself defines the context in which small and relevant portions of ontologies are mapped. We illustrate application of the proposed system in the context of Technology Enhanced Learning (TEL) where learners need to access to learning resources covering specific concepts.

Keywords: Resources query, ontologies, ontology mapping, similarity measures, semantic web, e-learning.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1339007

References:

[1] Euzenat, J., Shvaiko, P. Ontology matching: state of the art and future challenges (2nd ed.). Heidelberg (DE): Springer-Verlag. URL:http://book.ontologymatching.org (2013).
[2] Otero-Cerdeira, L., Rodreguez-Martinez, F. J. & Gomez-Rodriguez A.: Ontology matching: A literature review in a literature reviewExpert Systems with Applications, (2015).
[3] Euzenat, J., Le Bach, T., Barrasa, J., Bouquet, P., De Bo, J., Dieng- Kuntz, R., Ehrig, M., Hauswirth, M., Jarrar, M., Lara, R., Maynard, D., Napoli, A., Stamou, G., Stuckenschmidt H., Shvaiko, P., Tessaris, S., Van Acker, S., Zaihrayeu, I.: State of the art on ontology (2004).
[4] Bouzeghoub, A., Defude, B., Duitama, F. &Lecocq, C. (2006). /A Knowledge-Based Approach to Describe and Adapt Learning Objects/. International Journal on E-Learning. 5 (1*) *Special Issue: Learning Objects in Context, pp. 95-102. Chesapeake, VA: AACE (ISSN 1537- 2456).
[5] Bouzeghoub, A., Elbyed, A. Ontology Mapping for Web-Based Educational Systems Interoperability. IBIS (Interoperability in Business Information Systems), vol. 1, 73-84 (2006).
[6] Bouzeghoub, A., Elbyed, An ontology mapping algorithm to share learning resources. Information and Communication Technologies, 2006. ICTTA'06. 2nd 1, 616-621
[7] Java Agent Development Framework, http://jade.tilab.com/
[8] OntoBroker user guide, http://www.ontoprise.de/
[9] ACM Computing Classification System: Advancing Computing as a Science & Profession: available from http://www.acm.org/
[10] Euzenat, J. and Valtchev, P.: Similarity-Based Ontology Alignment in OWL-Lite. ECAI. Valencia, Spain IOS Press, 333-337 (2004)
[11] Albertoni, R., De Martino, M.:Semantic Similarity of Ontology Instances Tailored on the Application Context.In: Proceedings of ODBASE (2006).
[12] Bernstein, P., Melnik, S., Mork, P.:Interactive Schema Translation with Instance-Level Mappings.In: Proceedings of VLDB (Demonstration) (2005)
[13] Kotis, K., Valarakos, A., Vouros, G.: AUTOMS: Automating Ontology Mapping through Synthesis of Methods. OAEI (Ontology Alignment Evaluation Initiative) contest, Ontology Matching International Workshop, Atlanta, USA. (2006)
[14] Valarakos, A. G., Spiliopoulos, V., Kotis, K., Vouros G.:AUTOMS-F: A Java Framework for Synthesizing Ontology Mapping Methods. In: Proceedings of I-KNOW (2007).
[15] Kirsten, T., Thor, A., Rahm, E.: Instance-based matching of large life science ontologies.In: Proc. 4th Int. Workshop DILS(Data Integration in Life Sciences), LNCS, 172-187 (2007)
[16] Serafini, L., Tamilin, A.:Instance Migration in Heterogeneous Ontology Environments. In: Proceedings of ISWC+ASWC (2007)