An Ontology Representation Language for Multimedia Event Applications

  • Nisha Pahal Department of Electrical Engineering, Indian Institute of Technology, Delhi, India
  • Brejesh Lall Department of Electrical Engineering, Indian Institute of Technology, Delhi, India
  • Santanu Chaudhury Department of Electrical Engineering, Indian Institute of Technology, Delhi, India
Keywords: Multimedia web ontology language (MOWL), event, multimedia event ontology language (E-MOWL), Bayesian network (BN), inference


This paper presents formalization of a new Multimedia Web Ontology Language (E-MOWL) to handle events with media depictions. The temporal, spatial and entity aspects that are implicitly linked to an event are represented through this language to model the context of events. The already existing Multimedia Web Ontology Language (MOWL) can be leveraged for perceptual modelling of a domain, where the concepts manifest into media patterns in the multimedia document and helps in semantic processing of the contents. The language E-MOWL provides a rich method for representing knowledge corresponding to a specific domain wherein the context specifies the intended meaning of each element of the domain of discourse; an element in different context may correspond to different functional role. The context information associated with an event ties the audiovisual data with event related aspects. All these aspects when considered altogether provide the evidence and contribute towards recognizing an event from multimedia documents. The language also enables reasoning with the uncertainty associated with the events and is organized in the form of Bayesian Network (BN).
The media items that are semantically relevant can be assimilated together on the basis of their association with events. We have demonstrated the efficacy of our approach by utilizing an ontology for the entertainment category in news domain to offer an application \textit{news aggregation} and event-based book recommendations.


Download data is not yet available.

Author Biographies

Nisha Pahal, Department of Electrical Engineering, Indian Institute of Technology, Delhi, India

Nisha Pahal received the B.E. degree in computer science and engineering from the Lingayas University, Faridabad, India, in 2005, and the M.Tech. degree in computer engineering from the YMCA University of Science and Technology, Faridabad, India in 2007. She received her Ph.D. degree from the Indian Institute of Technology Delhi, India in the year 2017 and has many publications to her credit in reputed international conferences. In due course of Ph.D. degree, she has been a part of the industrial project on Context-aware reasoning framework for Multi-user recommendations in Smart Home.

She is currently working as an Assistant Professor at Amity University Noida, India. Her current research interests include Multimedia Analysis, Ontology, Bayesian Network, NLP, and Machine learning.

Brejesh Lall, Department of Electrical Engineering, Indian Institute of Technology, Delhi, India

Brejesh Lall (Member, IEEE) received the B.E. and the M.E. degrees in electronics and communication from Delhi College of Engineering, DU Delhi, India, in 1991, and 1992, respectively. He completed Ph.D. degree, in 1997 from IIT Delhi in the area of multirate signal processing. During the Ph.D. he worked on “some studies on characterization and modeling of stochastic processes in the multiscale framework.”

He joined Hughes Software Systems, in 1997 and worked there for nearly eight years with the Signal Processing Group. He returned to his alma mater and joined IIT Delhi as a faculty member, in 2005. Since July 2005, he has been in the Electrical Engineering Department and has contributed to research and teaching in the general area of Signal Processing. He has successfully completed numerous sponsored projects and consultancies and is working on several others. He is the current head of Bharti School of Telcom Technology and Management, and the co-ordinator of two centers of excellence, viz. Airtel IIT Delhi Centre of Excellence in Telecommunications and Ericsson IIT Delhi 5G Center of Excellence.

Santanu Chaudhury, Department of Electrical Engineering, Indian Institute of Technology, Delhi, India

Santanu Chaudhury received the B.Tech degree in electronics and electrical communication engineering, and the Ph.D. degree in computer science and engineering from the Indian Institute of Technology Kharagpur, Kharagpur, India, in 1984 and 1989, respectively.

He is a Professor with the Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India, and is currently serving as the Director with the Indian Institute of Technology Jodhpur, Jodhpur, India. Recently, he completed his tenure as the Director with the Central Electronics Engineering Research Institute, Pilani, India. He has more than 300 research publications in peer reviewed journals and conference proceedings, 15 patents, and four authored/edited books to his credit. His research interests include image and video processing, computer vision, machine learning, and embedded systems.

Prof. Chaudhury was the recipient of the Distinguished Alumnus award from the Indian Institute of Technology Kharagpur. He is a Fellow of the Indian National Academy of Engineering, the National Academy of Sciences, and the International Association for Pattern Recognition. He was awarded the Indian National Science Academy Medal for Young Scientists in 1993. He was also the recipient of the Advanced Computing and Communications Society-Centre for Development and Advanced Computing (ACCS-CDAC) award for his research contributions in 2012.


Blei, D. M. and Jordan, M. I. 2003. Modeling annotated data. Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, ACM, pp. 127–134.

Chaudhury, S., Mallik, A. and Ghosh, H. 2015. Multimedia Ontology: Representation and Applications, CRC Press, 2015.

Francois, A. R., Nevatia, R., Hobbs, J., Bolles, R. C. and Smith, J. R. 2005. Verl: an ontology framework for representing and annotating video events, MultiMedia, IEEE 12(4):76–86.

Ghosh, H. and Chaudhury, S. 2013. Ontology for semantic multimedia web.

Liu, W., Liu, Z., Fu, J., Hu, R. and Zhong, Z. 2010. Extending owl for modeling event-oriented ontology, Complex, Intelligent and Software Intensive Systems (CISIS), 2010 International Conference on, IEEE, pp. 581–586.

Neapolitan, R. E. 2012. Probabilistic reasoning in expert systems: theory and algorithms, CreateSpace Independent Publishing Platform.

Pahal, N., Chaudhury, S. and Lall, B. 2013. Extending mowl for event representation (e-mowl), Proceedings of the 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)-Volume 03, IEEE Computer Society, pp. 171–174.

Pahal, N., Chaudhury, S. and Lall, B. 2015. Context-based semantic tagging of multimedia data, International Conference on Pattern Recognition and Machine Intelligence, Springer, pp. 169–179.

Papadias, D., Mamoulis, N. and Delis, V. 2001. Approximate spatio-temporal retrieval. ACM Transactions on Information Systems (TOIS) 19(1):53–96.

Patel-Schneider, P. F., Hayes, P., Horrocks, I. et al. 2004. Owl web ontology language semantics and abstract syntax, W3C recommendation 10.

Pongpaichet, S., Singh, V. K., Gao, M. and Jain, R. 2013. Eventshop: recognizing situations in web data streams, Proceedings of the 22nd international conference on World Wide Web companion, International World Wide Web Conferences Steering Committee, pp. 1359–1368.

Scherp, A. and Mezaris, V. 2014. Survey on modeling and indexing events in multimedia, Multimedia Tools and Applications 70(1):7–23.

Shaw, R. and Larson, R. R. 2008. Event representation in temporal and geographic context, Research and Advanced Technology for Digital Libraries, Springer, pp. 415–418.

Wattamwar, S. S. and Ghosh, H. 2008. Spatio-temporal query for multimedia databases, Proceedings of the 2nd ACM workshop on Multimedia semantics, ACM, pp. 48–55.

Westermann, U. and Jain, R. 2006. E-a generic event model for event-centric multimedia data management in echronicle applications, Data Engineering Workshops, 2006. Proceedings 22nd International Conference on, IEEE, pp. x106–x106.

Westermann, U. and Jain, R. 2007. Toward a common event model for multimedia applications, IEEE MultiMedia 14(1):19–29.

Wu, L. n.d. Representing and inferring events from deforestation observations.