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Receiver-side semantic reasoning for digital TV personalization in the absence of return channels

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Abstract

Experience has proved that interactive applications delivered through Digital TV must provide personalized information to the viewers in order to be perceived as a valuable service. Due to the limited computational power of DTV receivers (either domestic set-top boxes or mobile devices), most of the existing systems have opted to place the personalization engines in dedicated servers, assuming that a return channel is always available for bidirectional communication. However, in a domain where most of the information is transmitted through broadcast, there are still many cases of intermittent, sporadic or null access to a return channel. In such situations, it is impossible for the servers to learn who is watching TV at the moment, and so the personalization features become unavailable. To solve this problem without sacrificing much personalization quality, this paper introduces solutions to run a downsized semantic reasoning process in the DTV receivers, supported by a pre-selection of material driven by audience stereotypes in the head-end. Evaluation results are presented to prove the feasibility of this approach, and also to assess the quality it achieves in comparison with previous ones.

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Notes

  1. http://www.dvb.org/technology/standards.

  2. http://eng.t-dmb.org.

  3. http://www.dvb-h.org.

  4. http://www.qualcomm.com/mediaflo.

  5. As explained for a server-based personalization engine in [10], the DOI for a given item can be explicitly entered by the viewer, or inferred from indirect measures such as the time he/she spends watching or executing it.

  6. The DOI of the attribute Age 14-16 is not influenced by \(\mathcal{P}_2\), because this program is not rated in \(\mathcal{S}_1\).

  7. For example, a carousel containing 4 MBytes of data, transmitted at a rate of 256 Kbps, takes 128 s to complete a cycle; so, it may take more than 2 min to load a particular piece of information.

  8. In a real scenario, the disappearance of a stereotype would mean that the group of viewers that it aims to represent should be a residual audience for the TV program in question.

  9. ATLAS is an acronym for “Architecture for T-Learning interActive Services”.

  10. http://www.mhp.org.

  11. ATTOS is an acronym for “ATlas, TOol Support”.

  12. http://www.dvb.org/technology/standards/.

  13. http://protege.stanford.edu/.

  14. http://backstage.bbc.co.uk.

  15. http://www.imdb.com.

  16. Thanks to the reuse capabilities of ATLAS (see [41]), 1.5 MBytes sufficed to deliver up to 20 courses at the same time.

  17. Interestingly, we could check that the ratings given by the viewers to courses they had classified as potentially appealing were lower than 5 only in 8% of the cases. This fact undoubtedly supports the validity of our estimation of recall.

  18. http://www.itu.int/ITU-T/IPTV/.

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Acknowledgements

This work has been partially funded by the Ministerio de Educación y Ciencia (Gobierno de España) project TSI2007-61599, by the Consellería de Educación e Ordenación Universitaria (Xunta de Galicia) incentives file 2007/000016-0, and by the Consellería de Innovación, Industria e Comercio (Xunta de Galicia) project PGIDIT05PXIC32204PN.

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Authors and Affiliations

  1. Department of Telematics Engineering, University of Vigo, ETSE Telecomunicación, Campus Universitario s/n, Vigo, 36310, Spain

    Martín López-Nores, Yolanda Blanco-Fernández, José J. Pazos-Arias, Jorge García-Duque, Manuel Ramos-Cabrer, Alberto Gil-Solla, Rebeca P. Díaz-Redondo & Ana Fernández-Vilas

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  1. Martín López-Nores
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Correspondence to Martín López-Nores.

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López-Nores, M., Blanco-Fernández, Y., Pazos-Arias, J.J. et al. Receiver-side semantic reasoning for digital TV personalization in the absence of return channels. Multimed Tools Appl 41, 407–436 (2009). https://doi.org/10.1007/s11042-008-0239-7

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