Ngamnij Arch-int, Chatkamon Anontachai

Show more
Semantic Mining Information Integration Laboratory (SMIL), Computer Science Department, Science Faculty, Khan Kaen University, Khan Kaen, Thailand..
Show less

Abstract: Presently, many museums have developed their own multimedia information systems to store the artifacts and other objects of scientific, artistic, cultural or historical interest into the digital resources and make them available for public viewing on the Web. However, searching for the multimedia information is still not relevant to the user requirement, and the system does not provide meaningful information. This research work proposes the personalized multimedia integration system for museums based on ontology which is a core component of the Semantic Web technology. The multimedia information for each resource has been expressed in the Web Ontology Language (OWL). The research also resolved the problem of information integration by proposing the ontology mapping technique to cope with the semantic conflicts and structural conflicts via the OWL properties. Then the ontology storing users’ interest was designed which matched the museum’s ontology so that retrieval of multimedia information is meaningful and direct to the users’ needs.

Keywords: Ontology Mapping; Personalized Multimedia Integration; Heterogeneous Museum Systems; Semantic Web

Cite this paper: N. Arch-int and C. Anontachai, "Personalized Multimedia Integration for the Heterogeneous Museum Systems Using the Ontology Mapping Approach," Journal of Service Science and Management, Vol. 5 No. 4, 2012, pp. 339-347. doi: 10.4236/jssm.2012.54040.

References

[1]   T. Berners-Lee, J. Hendler and O. Lassila, “The Semantic Web,” Scientific American, Vol. 284, No. 5, 2001, pp. 3443. doi:10.1038/scientificamerican0501-34

[2]   D. L. McGuinness and F. van Harmelen, “Owl: Web Ontology Language Overview,” 2011. http://www.w3.org/TR/owl-ref/

[3]   G. A. Miller, “WordNet: A Lexical Database for English,” Communications of the ACM, Vol. 11, No. 38, 1995, pp. 39-41. doi:10.1145/219717.219748

[4]   K. Wang, “Improving Engineering Data Management with Semantic Web Techniques,” Journal of Service Science and Management, Vol. 1, No. 3, 2008, pp. 199-205. doi:10.4236/jssm.2008.13021

[5]   O. Lassila and R. R. Swick, “Resource Description Framework (RDF) Model and Syntax Specification,” 2011. http://www.w3.org/RDF

[6]   D. Brickley and R. V. Guha, “Resource Description Framework Schema (RDFS),” 2011. http://www.w3.org/TR/PR-rdf-schema/

[7]   G. Karvounarakis, S. Alexaki, V. Christophides, D. Plexousakis and M. Scholl, “RQL: A Declarative Query Language for RDF,” Proceedings of World Wide Web, Honolulu, May 7-11, 2002, pp. 592-603.

[8]   W3C, “RDQL: A Query Language for RDF,” 2011. http://www.w3.org/Submission/RDQL/

[9]   E. P. Hommeaux and A. Seaborne, “SPARQL Query Language for RDF,” 2011. http://www.w3.org/TR/rdf-sparql-query/

[10]   R. Fikes, P. Hayes and I. Horrocks, “OWL-QL: A Language for Deductive Query Answering on the Semantic,” Web Semantics: Science, Services and Agents on the World Wide Web, Vol. 2, No. 1, 2004, pp. 19-29. doi:10.1016/S1570-8268(09)00054-7

[11]   Dublin Core, “The Dublin Core Metadata Initiative,” 2010. http://dublincore.org/

[12]   D. Beckett, E. Miller and D. Brickley, “Expressing Simple Dublin Core in RDF/XML,” 2010. http://dublincore.org/documents/dcmes-xml/

[13]   S. Kokkelink and R. Schw?nzl, “Expressing Qualified Dublin Core in RDF/XML,” 2010. http://dublincore.org/documents/dcq-rdf-xml/

[14]   J. L. Seng and I. L. Kong, “A Schema and OntologyAided Intelligent Information Integration,” Expert Systems with Applications, Vol. 36, No. 7, 2009, pp. 1053810550. doi:10.1016/j.eswa.2009.02.067

[15]   W. May and G. Lausen, “A Uniform Framework for Integration of Information from the Web,” Information System, Vol. 29, No. 1, 2004, pp. 59-91. doi:10.1016/S0306-4379(03)00005-X

[16]   S. Bergamaschi, S. Castano, M. Vincini and D. Beneventano, “Semantic Integration of Heterogeneous Information Sources,” Data & Knowledge Engineering, Vol. 36, No. 3, 2001, pp. 215-249. doi:10.1016/S0169-023X(00)00047-1

[17]   S. Zhu and J. Feng, “Using an Ontology to Help Reason about the Information Content of Data,” Journal of Software Engineering and Applications, Vol. 3, No. 7, 2010, pp. 629-643. doi:10.4236/jsea.2010.37073

[18]   S. Ram and J. Park, “Semantic Conflict Resolution Ontology (SCROL): An Ontology for Detecting and Resolving Data and Schema-Level Semantic Conflicts,” IEEE Transactions on Knowledge and Data Engineering, Vol. 16, No. 2, 2004, pp. 189-202. doi:10.1109/TKDE.2004.1269597

[19]   D. Sánchez, M. Batet, D. Isern and A. Valls, “Ontology-Based Semantic Similarity: A New Feature-Based Approach,” Expert Systems with Applications, Vol. 39, No. 9, 2012, pp. 7718-7728. doi:10.1016/j.eswa.2012.01.082

[20]   H. Liu, H. Bao and D. Xu, “Concept Vector for Semantic Similarity and Relatedness Based on WordNet Structure,” Journal of Systems and Software, Vol. 85, No. 2, 2012, pp. 370-381. doi:10.1016/j.jss.2011.08.029

[21]   C. Li and T. W. Ling. “OWL-Based Semantic Conflicts Detection and Resolution for Data Interoperability,” Lecture Notes in Computer Science, Springer, New York, 2004, pp. 266-277.

[22]   Y. Kalfoglou and M. Chorlemmer, “Ontology Mapping: The State of the Art,” The Knowledge Engineering, Vol. 18, No. 1, 2003, pp. 1-31. doi:10.1017/S0269888903000651

[23]   D.-N. Chen and Y.-C. Chiang, “Combining Personal Ontology and Collaborative Filtering to Design a Document Recommendation System,” Journal of Service Science and Management, Vol. 2, No. 4, 2009, pp. 322-328. doi:10.4236/jssm.2009.24038

[24]   X. Aimé, F. Furst, P. Kuntz and F. Trichet, “Prototypicality Gradient and Similarity Measure: A Semiotic-Based Approach Dedicated to Ontology Personalization,” Intelligent Information Management, Vol. 2, No. 2, 2010, pp. 65-79. doi:10.4236/iim.2010.22009

[25]   B. Solomon, “Using Web Services to Deliver Information Integration,” Proceedings of the Museums and the Web Conference, Albuquerque, 22-25 March 2006.

[26]   O. Signore, “Ontology Driven Access to Museum Information,” Proceedings of the Annual Conference of CIDOC, Zagreb, 24-27 May 2005, pp. 1-8.

[27]   E. Sirin, B. Parsia, B. C. Grau, A. Kalyanpur and Y. Katz, “Pellet: A Practical OWL-DL Reasoned,” Journal of Web Semantics, Vol. 5, No. 2, 2007, pp. 51-55. doi:10.1016/j.websem.2007.03.004

[28]   V. Jalali and A. Bagheri, “Semi-Automated Mapping from RDB to Ontology,” Proceedings of the 3rd International Conference on Information & Knowledge Technology, Mashhad, 27-29 November 2007.

[29]   N. Cullot, R. Ghawi and K. Yétongnon, “DB2OWL: A Tool for Automatic Database-to-Ontology Mapping,” Proceedings of the 15th Italian Symposium on Advanced Database Systems, Torre Canne, 17-20 June 2007, pp. 491-494.

[30]   C. Courtney and M. Rada, “Measuring the Semantic Similarity of Texts,” Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment, Ann Arbor, 30 June 2005, pp. 13-18.

[31]   C. J. van Rijsbergen, “Information Retrieval,” Butterworths, London, 1975.