Email this article 
Open Access
Subscription or Fee Access
Implementing Semantics Using Fuzzy Ontology
Abstract
Educational data mining is a fast and non linear process, which is now widely applied in distributed and dynamic environments such as on the world wide web. Semantic matching is the important problem in educational mining. In this research work, a framework for semantic matching that is used to identify the growth of students dynamically and implemented. In order to generate semantic matching the input text is divided into tags using tag generator. The tags are given to filter word remover in order to perform effective filter word deductions and parts of voice recognizer. Semantic generator is generated based on input tags.Temporal and inverse temporal are computed and then single value is calculated. Educational data mining has proved to be an effective way of delivering materials to previous unreachable students under previously impossible circumstances with previous unavailable access and presentation methods. The success stories of e-learning conferences and e-learning community speak for the glory. Educational data mining facilitate adaptive learning such that instructors can dynamically revise and deliver instructional materials in accordance with learner’s current progress. In general,adaptive teaching and learning refers to the use of what is known about learners, a priority through interactions, to alter how a learning experience unfolds, with the aim of improving learner’s success and satisfaction.
Keywords
References
Xiang Li, Ling Feng, Lizhu Zhou, Yuanchun Shi, “Learning in an Ambient Intelligent World: Enabling Technologies and Practices,”IEEE Transactions on Knowledge and Data Engineering, Vol.21,No.6,pp,910-924,June,2009.
Zhaohui Wu Yuxin Mao Huajun Chen “ Subonology-Based Resource Management for Web-Based e-learning” IEEE Transactions on Knowledge and Data Engineering, Vol.21,No 6,pp 867-880,June 2009.
Amal Zouaq and Roger Nkambou, “Enhancing Learning Objects with an Ontology-Based Memory” IEEE Transactions on Knowledge and Data Engineering, Vol.21, No.6, pp.881 893, June, 2009.
Toward a Fuzzy Domain Ontology ExtractionMethod for Adaptive e-Learning Raymond Y.K. Lau, Senior Member, IEEE, Dawei Song,Yuefeng Li, Member, IEEE,Terence C.H. Cheung, Member, IEEE,and Jin-Xing Hao IEEE Transactions Knowledge and data engineering, vol. 21, no. 6, june 2009
Patrick Perrin and Frederick Petry, “Extraction and Representation of Contextual Information for Knowledge Discovery in Texts,”Information Sciences, Vol.151, pp.125 152, 2003.
Mgeorge Furnas, Scott Deerwester, Susan T.Dumais, Thomass K.Landauer, Richard Harshman, Lynn A. Streeter, and Karen E.Lochbaum, “Information Retrieval using a Singular Value Decomposition Model of Latent Semantic Structure”. In editor,Proceedings of the 11th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp.465-480.
Hongyan Jing and Evelyne Tzoukermann, “Information Retrieval Based on Context Distance and Morphology,” In Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in information Retrieval, Language Analysis,pp,90-96,1999.
RYK Lau,D Song,Y Li,TCH Cheung,JX Hao-“Towards a Fuzzy Domain Ontology Extraction Method for Adaptive e Learning “ IEEE Transactions on Knowledge and Data, Vol.21, No.6,pp 800-813,June 2009.
G.A.Miller, Beckwith R., C.Fellbaum,D.Gross, and K.J.Miller,”Introcution to Wordnet: An On-Line Lexical Database.”Journal of Lexicography, Vol.3, No.4, pp.234 244.2009.
Hendler, Jim, “Agents and the Semantic Web,” IEEE Intelligent Systems. March/April 2001 (Vol. 16, 2).
Horrocks, I. Et al – OilED, available on the WWW at http://img.cs.man.ac.uk/oil/
M. A. Musen, R. W. Fergerson, W. E. Grosso, N. F. Noy, M. Crubezy,& J. H. Gennari. “Component-Based Support for Building Knowledge-Acquisition Systems”. In Conference on Intelligent Information Processing (IIP 2000) of the International Federation for Information Processing World Computer Congress (WCC 2000),Beijing, 2000.
McGuinness, D. "Conceptual Modeling for Distributed Ontology Environments." Proceedings of the Eighth International Conference on Conceptual Structures Logical, Linguistic, and Computational Issues (ICCS 2000). Darmstadt, Germany. August 14-18, 2000.
K. Stoffel, M. Taylor, J. Hendler. “Efficient Management of Very Large Ontologies.” In Proceedings of American Association for Artificial Intelligence Conference (AAAI-97), AAAI/MIT Press 1997.
Y. Sure, M. Erdmann, J. Angele, S. Staab, R. Studer, D.Wenke.OntoEdit: “Collaborative Ontology Development for the Semantic Web.” In Proceedings of the 1st International Semantic Web Conference - ISWC2002, Springer, LNCS. Baader, F., Horrocks, I.& Sattler, U. (2003).
Description Logics as Ontology Languages For the Semantic Web.Lecture Notes in Artificial Intelligence. Springer.Berendt B., Hotho A. & Stumme G (2002).
Towards Semantic Web Mining. Proceedings of First International Semantic Web Conference (ISWC), Sardinia, Italy, June 9-12, 264-278.
Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web.Scientific American, 284(5), 34-43.Bisson, G., Nedellec, C &,Canamero, L. (2000).
Designing clustering methods for ontology building - The Mo’K workbench. Proceedings of the ECAI Ontology Learning Workshop.Brickley, D. & Guha, R.V. (2003).RDF Vocabulary Description Language 1.0: RDF Schema. World Wide Web Consortium. http://www.w3.org/TR/rdf-schema/
Gomez-Perez, A., Fernandez-Lopez , M. & Corcho O. (2003)Ontological Engineering. Springer. Gomez-Perez, A. & Rojas, M.D. (1999) Ontological Reengineering and Reuse. 11th European Workshop on Knowledge Acquisition, Modeling and Management(EKAW’99, Germany). Lecture Notes in Artificial Intelligence LNAI 1621 Springer-Verlag, 139-156, eds., Fensel D. & Studer R.
Guarino N. (1998) Formal Ontology in Information Systems. First international conference on formal ontology in information systems,Italy, Ed. Guarino, 3-15.
Gruber, T. (August 1993).Toward principles for the design of ontologies used for knowledge sharing. International Journal of Human-Computer Studies, special issue on Formal Ontology in Conceptual Analysis and Knowledge Representation. Eds, Guarino, N.& Poli , R.
Grüninger, M. & Fox , M.S. (1995) Methodology for the design and evaluation of ontologies.
IJCAI’95 Workshop on Basic Ontological Issues in Knowledge Sharing, Canada. Ed. Skuce, D.)Halevy, A.Y. (2001) Answering queries using views: A survey. The VLDB Journal, 10(4),270–294.
Hameed, A., Preece, A. & Sleeman, D. (2004) Ontology Reconciliation. Handbook on Ontologies. Eds. Staab, S. & Studer,R.,231-250.
Harsleev V. & Möller R.. (2001) Racer system description. Proc. of the Int. Joint Conf. on automated reasoning (IJCAR 2001). Lecture Notes in Artificial Intelligence 2083, 701-705, Springer.
Heflin J. (2004) OWL Web Ontology Language Use Cases and Requirements. W3C Recommendation.WWW.W3.org.
Horrocks I. (2002) DAML+OIL: a reasonable Web ontology language.Proc. of EDBT 2002, Lecture Notes in Computer Science 2287, 2-13,Springer.
R. Bergmann and M. Schaaf, “Structural Case-Based Reasoning and Ontology-Based Knowledge Management: A Perfect Match?”, J.Universal Computer Science (UCS), vol. 9, no. 7, pp. 608-626, 2003.
F. Baader, The Description Logic Handbook: Theory, Implementation and Applications. Cambridge Univ. Press, Jan. 2003.
M. Klusch, B. Fries, and K. Sycara, “OWLS-MX: A Hybrid Semantic Web Service Matchmaker for OWL-S Services,” WebSemantics:Science, Services, and Agents on the World Wide Web, vol. 7, no. 2,pp. 121-133, Apr. 2009.
Enabling Semantic Web Services: The Web Service Modeling Ontology,D. Fensel, H. Lausen, A. Polleres, J.D. Bruijn, M.Stollberg,D. Roman, and J. Domingue, eds. Springer-Verlag, 2006.
OWL, http://www.w3.org/2004/OWL/, 2004.
OWL-S 1.1Release:Examples,http://www.daml.org/services/owls/ 1.1/examples.html, 2004.
A.M. Zaremski and J.M. Wing, “Specification Matching of Software Components,” Proc. Third ACM SIGSOFT Symp. Foundations of Software Eng., pp. 6-17, 1995.
UDDI, www.oasis-open.org/committees/uddi-spec, 2005.
Bruner, Jerome.S. 1967. On knowing: Essays for the left hand.Cambridge, Harvard University Press.
Kiley, M. et al.,2007. Problem Based Learning. The University of Adelaide. Australia. http://www.adelaide.edu.au/clpd/resources/leap/leapinto
/ProblemBasedLearning.pdf. Accessed: 20 March 2008.
Shannon, Bill. (2003). Java 2 Platform Enterprise Edition
Specification, v1.4. http://java.sun.com/j2ee/j2ee-1_4-fr spec.pdf.Accessed: 10 January 2008.
Gruber, Tom. 2007. What is an Ontology?. http://wwwksl.stanford.edu/kst/what-is-an-ontology.html. Accessed:25 March 2008.
JENA – A Semantic Web framework for Java. http://jena.sourceforge.net /documentation.html Accesed: 10 June 2008.
Seaborne, Andy. Prud’hommeaux, Eric. 2008 “SPARQL Query Language for RDF” http://www.w3.org/TR/rdf-sparql query/ .Accessed: 09 August 2008.
Laclavik, Michal. Balogh, Zoltan. Babik, Marian. 2006. AgentOWL:Semantic Model and agent architecture. Computing and informatics, Vol. 25, Pp. 419-437.
Bellifemine, F. et al., 2007. JADE Programmer’s Guide - Java agent development framework. http://jade.tilab.com. Accessed: 20 July2008.
Nilsen, Jaran. 2008. Jade4Spring. http://jade4spring.sourceforge.net/index.html. Accessed.
Stanford Center for Biomedical Informatics Research. 2008.Protégé.http://protege.stanford.edu/doc/users.html#tutorials.Accessed: 5 September 2008.
P. Haase, J. Broekstra, A. Eberhart, and R. Volz, “A comparison of RDF query languages,” in: ISWC 2004, LNCS 3298, Springer-Verlag Berlin Heidelberg, 2004, pp. 502–517.
T. Furche, B. Linse, F. Bry, D. Plexousakis, and G. Gottlob, “RDF querying: language constructs and evaluation methods compared,” in:Reasoning Web 2006, LNCS 4126, Springer-Verlag Berlin Heidelberg, 2006, pp. 1–52.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.