Nothing Special   »   [go: up one dir, main page]

skip to main content
research-article

MOWL: An ontology representation language for web-based multimedia applications

Published: 27 December 2013 Publication History

Abstract

Several multimedia applications need to reason with concepts and their media properties in specific domain contexts. Media properties of concepts exhibit some unique characteristics that cannot be dealt with conceptual modeling schemes followed in the existing ontology representation and reasoning schemes. We have proposed a new perceptual modeling technique for reasoning with media properties observed in multimedia instances and the latent concepts. Our knowledge representation scheme uses a causal model of the world where concepts manifest in media properties with uncertainties. We introduce a probabilistic reasoning scheme for belief propagation across domain concepts through observation of media properties. In order to support the perceptual modeling and reasoning paradigm, we propose a new ontology language, Multimedia Web Ontology Language (MOWL). Our primary contribution in this article is to establish the need for the new ontology language and to introduce the semantics of its novel language constructs. We establish the generality of our approach with two disperate knowledge-intensive applications involving reasoning with media properties of concepts.

Supplementary Material

a8-mallik-apndx.pdf (mallik.zip)
Supplemental movie, appendix, image and software files for, MOWL: An ontology representation language for web-based multimedia applications

References

[1]
Arndt, R., Troncy, R., Staab, S., Hardman, L., and Vacura, M. 2007. COMM: designing a well-founded multimedia ontology for the web. In Proceedings of the 6th International Semantic Web Conference (ISWC'07/ASWC'07). Springer-Verlag, Berlin, 30--43.
[2]
Bai, L., Lao, S., Jones, G. J. F., and Smeaton, A. F. 2007. Video semantic content analysis based on ontology. In Proceedings of the International Machine Vision and Image Processing Conference (IMVIP'07). IEEE Computer Society, Los Alamitos, CA, 117--124.
[3]
Bertini, M., Bimbo, A. D., Serra, G., Torniai, C., Cucchiara, R., Grana, C., and Vezzani, R. 2009. Dynamic pictorially enriched ontologies for digital video libraries. Multimedia 16, 2, 42--51.
[4]
Busa-Fekete, R., Szarvas, Gy., Éltetö, T., and Kégl, B. 2012. An apple-to-apple comparison of Learning-to-rank algorithms in terms of normalized discounted cumulative gain. In Proceedings of the ECAI-12 Workshop, Preference Learning: Problems and Applications in AI (ECAI-12). IEEE Computer Society.
[5]
Chaudhury, S. and Ghosh, H. 2004. Distributed and reactive query planning in RMAGIC: An agent based multimedia retrieval system. IEEE Trans. Knowle. Data Eng. 16, 9, 1082--1095.
[6]
Dasiopoulou, S., Kompatsiaris, I., and Strintzis, M. G. 2010. Investigating fuzzy DLs-based reasoning in semantic image analysis. Multimed. Tools Appl. 49, 1, 167--194.
[7]
Ding, Z. and Peng, Y. 2004. A probabilistic extension to ontology language OWL. In Proceedings of the 37th Hawaii International Conference on System Sciences.
[8]
Doerr, M. 2012. The CIDOC conceptual reference module: An ontological approach to semantic interoperability of metadata. AI Mag. 24, 3.
[9]
Foley, J. D., van Dam, A., Feiner, S. K., and Hughes, J. F. 1982. Computer Graphics: Principles and Practice.
[10]
Gangemi, A., Guarino, N., Masolo, C., Oltramari, A., and Schneider, L. 2002. Sweetening ontologies with DOLCE. In Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web (EKAW'02), Springer-Verlag. 166--181.
[11]
Garcia, R. and Celma, O. 2005. Semantic integration and retrieval of multimedia metadata. In Proceedings of the 5th Knowledge Markup and Semantic Annotation Workshop (SemAnnot'05).
[12]
Ghosh, H., Chaudhury, S., Kashyap, K., and Maiti, B. 2007. Ontology specification and integration for multimedia applications. In Ontologies: A Handbok of Principles, Concepts, and Applications in Information Systems. Springer.
[13]
Hunter, J. 2003. Enhancing the semantic interoperability of multimedia through a core ontology. IEEE Trans. Circ. Syst. Video Tech. 13, 1, 49--58.
[14]
Jiang, S., Huang, T., and Gao, W. 2004. An ontology based approach to retrieve digitized art images. In Proceedings of the IEEE International Conference on Web Intelligence. 131--137.
[15]
Kangassalo, H. 1991. Conceptual level user interfaces to data bases and information systems. In Advances in Information Modelling and Knowledge Bases. H. Jaakkola, H. Kangassalo, and S. Ohsuga, Eds., IOS Press, 66--90.
[16]
Kentner, B. 1979. Color Me a Season: A Complete Guide to Finding Your Best Colors and How to Use Them. Ken Kra Publishers.
[17]
Liu, S., Feng, J., Song, Z., Zhang, T., Lu, H., Xu, C., and Yan, S. 2012. Hi, magic closet, tell me what to wear! In Proceedings of the 20th ACM International Conference on Multimedia (MM'12). ACM, New York, 619--628.
[18]
Mallik, A., Chaudhury, S., and Ghosh, H. 2011. Nrityakosha: Preserving the intangible heritage of Indian classical dance. ACM J. Comput. Cultur. Herit. 4, 3, 11.
[19]
Motik, B., Patel-Schneider, P. F., and Parsia, B. 2012. OWL 2 Web ontology language: Structural specification and function-style syntax. http://www.w3.org/TR/owl2-syntax/.
[20]
Nikolopoulos, S., Paradopoulos, G., Kompatsiaris, I., and Patras, I. 2011. Evidence-driven image interpretation by combining implicit and explicit knpwledge in Bayesian Network. IEEE Trans. Syst. Man Cybernet. -- Part B 41, 5, 1366--1381.
[21]
Papadias, D. and Delis, V. M. 2001. Approximate spatio-temporal retrieval. ACM Trans. Inf. Syst. 19, 1, 53--96.
[22]
Patel-Schneider, P. F. and Horrocks, I. 2004. OWL web ontology language: Semantics and abstract syntax: section 2. abstract syntax. http://www.w3.org/TR/owl-semantics/syntax.html.
[23]
Pradhan, M., Henrion, M., Provan, G., Favero, B. D., and Huang, K. 1996. The sensitivity of belief networks to imprecise probabilities: an experimental investigation. Artif. Intell. 85, 363--397.
[24]
Rafatirad, S., Gupta, A., and Jain, R. 2009. Event composition operators: ECO. In Proceedings of the 1st ACM International Workshop on Events in Multimedia (EiMM'09). ACM, New York, 65--72.
[25]
Randell, D., Witkowski, M., and Shanahan, M. 2001. From images to bodies: Modelling and exploiting spatial occlusion and motion parallax. In Proceedings of the 17th International Joint Conference on Artificial Intelligence (IJCAI'01). Vol. 1 Morgan Kaufmann Publishers Inc., San Francisco, CA, 57--63.
[26]
Saathoff, C. and Scherp, A. 2010. Unlocking the semantics of multimedia presentations in the web with the multimedia metadata ontology. In Proceedings of the 19th International Conference on World Wide Web (WWW'10). ACM, New York, 831--840.
[27]
Salembier, P. and Smith, J. R. 2001. MPEG-7 multimedia description schemes. IEEE Trans. Circ. Syst. Video Tech. 11, 6, 748--759.
[28]
Scherp, A., Franz, T., Saathoff, C., and Staab, S. 2009. F--a model of events based on the foundational ontology dolce+DnS ultralight. In Proceedings of the 5th International Conference on Knowledge Capture (K-CAP'09). ACM, New York, 137--144.
[29]
Schneider, L. 2003. Designing foundational ontologies - The object-centered high-level reference ontology OCHRE as a case study. In Proceedings of the 22nd International Conference on Conceptual Modeling. Springer, 91--104.
[30]
Shaw, R., Troncy, R., and Hardman, L. 2009. LODE: Linking Open Descriptions of Events. In Proceedings of the 4th Asian Conference on the Semantic Web (ASWC'09). Springer-Verlag, Berlin, 153--167.
[31]
Tsinaraki, C., Polydoros, P., and Christodoulakis, S. 2007. Interoperability support between MPEG-7/21 and OWL in DS-MIRF. IEEE Trans. Knowl. Data Eng. 19, 2, 219--232.
[32]
Vogiatzis, D., Pierrakos, D., Paliouras, G., Jenkyn-Jones, S., and Possen, B. J. H. H. A. 2012. Expert and community based style advice. Expert Syst. Appli.: An Internat. J. 39, 12, 10647--10655.
[33]
Wattamwar, S. S. and Ghosh, H. 2008. Spatio-temporal query for multimedia databases. In Proceeding of the 2nd ACM Workshop on Multimedia Semantics, International Multimedia Conference, 48--55.

Cited By

View all
  • (2023)An Ontology for Spatio-Temporal Media Management and an Interactive ApplicationFuture Internet10.3390/fi1507022515:7(225)Online publication date: 23-Jun-2023
  • (2022)Digitizing Intangible Cultural Heritage Embodied: State of the ArtJournal on Computing and Cultural Heritage 10.1145/349483715:3(1-20)Online publication date: 16-Sep-2022
  • (2020)Machine Learning based Improved Gaussian Mixture Model for IoT Real-Time Data AnalysisIngeniería Solidaria10.16925/2357-6014.2020.01.0216:1Online publication date: 23-Jan-2020
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications
ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 10, Issue 1
December 2013
166 pages
ISSN:1551-6857
EISSN:1551-6865
DOI:10.1145/2559928
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 December 2013
Accepted: 01 April 2013
Revised: 01 July 2012
Received: 01 October 2011
Published in TOMM Volume 10, Issue 1

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Bayesian networks
  2. Multimedia web ontology language
  3. concept recognition
  4. digital heritage
  5. multimedia ontology
  6. recommendation engine

Qualifiers

  • Research-article
  • Research
  • Refereed

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)4
  • Downloads (Last 6 weeks)0
Reflects downloads up to 20 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2023)An Ontology for Spatio-Temporal Media Management and an Interactive ApplicationFuture Internet10.3390/fi1507022515:7(225)Online publication date: 23-Jun-2023
  • (2022)Digitizing Intangible Cultural Heritage Embodied: State of the ArtJournal on Computing and Cultural Heritage 10.1145/349483715:3(1-20)Online publication date: 16-Sep-2022
  • (2020)Machine Learning based Improved Gaussian Mixture Model for IoT Real-Time Data AnalysisIngeniería Solidaria10.16925/2357-6014.2020.01.0216:1Online publication date: 23-Jan-2020
  • (2020)Accomplishment of Multimedia Ontology for the Tunisian Archaeology FieldProceedings of Fifth International Congress on Information and Communication Technology10.1007/978-981-15-5859-7_5(64-72)Online publication date: 1-Oct-2020
  • (2020)ReferencesComputational Models for Cognitive Vision10.1002/9781119527886.refs(187-213)Online publication date: 6-Jul-2020
  • (2019)Towards a Multimedia Ontology for Tunisian Archaeology Field2019 7th International conference on ICT & Accessibility (ICTA)10.1109/ICTA49490.2019.9144900(1-6)Online publication date: Dec-2019
  • (2018)Extracting semantic knowledge from web context for multimedia IRMultimedia Tools and Applications10.1007/s11042-017-4997-y77:11(13853-13889)Online publication date: 1-Jun-2018
  • (2018)Digitization of Disaster Management: A Multimedia Ontological ApproachInformation and Communication Technology for Competitive Strategies10.1007/978-981-13-0586-3_20(197-203)Online publication date: 31-Aug-2018
  • (2018)Ontology-Driven Content-Based Retrieval of Heritage ImagesHeritage Preservation10.1007/978-981-10-7221-5_8(143-160)Online publication date: 16-Jun-2018
  • (2018)A Survey on IoT Based Traffic Control and Prediction MechanismInternet of Things and Big Data Analytics for Smart Generation10.1007/978-3-030-04203-5_4(53-75)Online publication date: 31-Dec-2018
  • Show More Cited By

View Options

Login options

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media