Abstract
In order to support the demands of fast and precise TV categorization for a personalized Electronic Programming Guide (EPG), the authors propose a new multidimensional taxonomy for the TV content. In addition to being much more lightweight in nature than the approach proposed by TV Anytime, with this method, a much more streamlined format is generated, which attempts to balance sensitive and detailed categorization criteria with computer efficiency in order to fulfill the demands of the recommender system. Furthermore, the authors propose a mechanism to obtain a quick and efficient real-time comparison of specific TV content with an alternative system called TV content fingerprinting
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Butkus, A., Petersen, M.: Semantic Modelling Using TV-Anytime Genre Metadata, pp. 226–234 (2007)
ETSI TS 102 822-3-1: TV-Anytime; Part 3: Metadata; 1 Sub-part 1: Part 1 - Metadata schemas (2006)
Pogacnik, M., Tasic, J., Meza, M., Kosir, A.: Personal Content Recommender Based on a Hierarchical User Model for the Selection of TV Programmes. User Modeling and User-Adapted Interaction 15(5), 425–457 (2005)
Castañares, W.: La televisión y sus géneros,?’una teoría imposible? CIC, Servicio de publicaciones UCM (3), 167–181 (1997)
Burke, R.: Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction 12(4), 331–370 (2002)
Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734–749 (2005)
Pogacnik, M., Tasic, J., Meza, M., Kosir, A.: Personal Content Recommender Based on a Hierarchical User Model for the Selection of TV Programmes. User Modeling and User-Adapted Interaction 15(5), 425–457 (2005)
Fernandez, Y.B., Arias, J.J.P., Nores, M.L., Solla, A.G., Cabrer, M.R.: AVATAR: An improved solution for personalized TV based on semantic inference. IEEE Transactions on Consumer Electronics 52(1), 223–231 (2006)
Bueno, D., Conejo, R., Recuenco, J.G.: TV Recommender System Architecture. In: Cesar, P., Chorianopoulos, K., Jensen, J.F. (eds.) EuroITV 2007. LNCS, vol. 4471, pp. 117–122. Springer, Heidelberg (2007)
The Science of Fingerprints, available at Project Gutenberg (2006), http://www.gutenberg.org/etext/19022
Baggaley, J.P., Duck, S.W.: Dynamics of Television. Westmead, Farnboroug, Hants: Saxon House, Tekfield Limited (1976)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Recuenco, J., Rojo, N., Bueno, D. (2008). A New Approach for a Lightweight Multidimensional TV Content Taxonomy: TV Content Fingerprinting. In: Tscheligi, M., Obrist, M., Lugmayr, A. (eds) Changing Television Environments. EuroITV 2008. Lecture Notes in Computer Science, vol 5066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69478-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-540-69478-6_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69477-9
Online ISBN: 978-3-540-69478-6
eBook Packages: Computer ScienceComputer Science (R0)