Skip to main content
Log in

PersonalTV

A TV recommendation system using program metadata for content filtering

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

This paper presents an approach to build a TV recommendation system called PersonalTV that enables the use of multiple classifiers, each one specialized on selected attributes of detailed program information. For generating adequate recommendations, the system makes use of content filtering and the preferences directly specified by the user within an MPEG-7 profile. By tracking user actions and interpreting their semantics, the system is able to individually weight these actions and dynamically adjusts the process to the user’s evolving preferences. We show how specialized spam fighting methods can successfully be transferred to the area of recommendation systems and adapted accordingly. Being lightweight, these methods are especially applicable in resource-constrained environments such as TV set-top boxes or mobile devices. Moreover, the use of the variance of the beta-distribution as a confidence value for each recommendation is presented.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Notes

  1. TV Guide Plus+ - http://www.europe.guideplus.com/

  2. TV Movie - http://www.tvmovie.de/

  3. TiVo - http://www.tivo.com/

  4. MY Personal TV Digital - http://mypersonaltvdigital.net/

  5. XMLTV—http://www.xmltv.org/

  6. Freevo—http://freevo.sourceforge.net/

  7. MythTV—http://www.mythtv.org/

  8. MeediOS—http://www.meedios.com/

  9. SageTV—http://www.sagetv.com/

  10. BeyondTV—http://www.snapstream.com/products/beyondtv/

  11. Video Disk Recorder—http://www.cadsoft.de/vdr/

  12. International Movie Database—http://www.imdb.com/

  13. TV250—http://www.tv250.de/

  14. Eplists—http://eplists.constabel.net/

  15. TV Addicted—http://www.tvaddicted.de/

References

  1. Ali K, van Stam W (2004) Tivo: making show recommendations using a distributed collaborative filtering architecture. In: KDD ’04: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, New York, pp 394–401

    Chapter  Google Scholar 

  2. Bär A, Berger A, Egger S, Schatz R (2008) A lightweight mobile tv recommender. In: Tscheligi M, Obrist M, Lugmayr A (eds) EuroITV. Lecture notes in computer science, vol 5066. Springer, New York, pp 143–147

    Google Scholar 

  3. Bernhaupt R, Wilfinger D, Weiss A, Tscheligi M (2008) An ethnographic study on recommendations in the living room: implications for the design of itv recommender systems. In: EuroITV, pp 92–101

  4. Cleland-Huang J, Mobasher B (2008) Using data mining and recommender systems to scale up the requirements process. In: ULSSIS ’08: Proceedings of the 2nd international workshop on Ultra-large-scale software-intensive systems. ACM, New York, pp 3–6

    Chapter  Google Scholar 

  5. European Telecommunications Standards Institute (2006) ETSI TS 102 822-3-1: broadcast and on-line services: search, select, and rightful use of content on personal storage systems (“TV-Anytime”); Part 3: metadata; Sub-part 1: phase 1 - metadata schemas. European Telecommunications Standards Institute, Sophia Antipolis

  6. European Telecommunications Standards Institute (2008) ETS ES 300 468: digital video broadcasting (DVB); specification for service information (SI) in DVB systems . European Telecommunications Standards Institute, Sophia Antipolis

  7. Fisher RA (1954)Statistical methods for research workers. Oliver and Boyd, Edinburgh

    Google Scholar 

  8. Garfinkel R, Gopal R, Pathak B, Yin F (2008) Shopbot 2.0: integrating recommendations and promotions with comparison shopping. Decis Support Syst 46(1):61–69

    Article  Google Scholar 

  9. Gotardo RA, Teixeira CAC, Zorzo SD (2008) Ip2 model—content recommendation in web-based educational systems using user’s interests and preferences and resources’ popularity. In: COMPSAC ’08: proceedings of the 2008 32nd annual IEEE international computer software and applications conference. IEEE Computer Society, Washington, DC, pp 460–463

    Chapter  Google Scholar 

  10. Graham P (2002) A Plan for spam. http://www.paulgraham.com/spam.html

  11. Graham P (2003) Better Bayesian filtering. http://www.paulgraham.com/better.html

  12. Graham P (2004) Hackers and painters: big ideas from the computer age. O’Reilly Media, Sebastopol

    Google Scholar 

  13. Gude M, Grünvogel SM, Pütz A (2008) Predicting future user behaviour in interactive live tv. In: EuroITV, pp 117–121

  14. ISO/IEC (2004) Information technology—multimedia content description interface—part 5: multimedia description schemes—final proposed draft admendment 2 of iso/iec 15938-5, n6398. http://www.chiariglione.org/mpeg/

  15. Leino J, Räihä K-J (2007) Case amazon: ratings and reviews as part of recommendations. In: RecSys ’07: Proceedings of the 2007 ACM conference on Recommender systems. ACM, New York, pp 137–140

    Chapter  Google Scholar 

  16. Louis G (2003) Bogofilter calculations: comparing bayes chain rule with fisher’s method for combining probabilities. http://www.bgl.nu/bogofilter/BcrFisher.html

  17. Louis G (2003) Testing bogofilter’s calculation methods. http://www.bgl.nu/bogofilter/test6000.html

  18. Manning CD, Raghavan P, Schütze H (2008) Introduction to information retrieval. Cambridge University Press, New York

    MATH  Google Scholar 

  19. Martinez JM (2003) MPEG-7 overview. ISO/IEC JTC1/SC29/WG11, Pattaya

  20. Melville P, Mooney RJ, Nagarajan R (2001) Content-boosted collaborative filtering. In: Proceedings of the 2001 SIGIR workshop on recommender systems

  21. Papanikolaou KA, Mabbott A, Bull S, Grigoriadou M (2006) Designing learner-controlled educational interactions based on learning/cognitive style and learner behaviour. Interact Comput 18(3):356–384

    Article  Google Scholar 

  22. Reimers U (2008) DVB—Digitale Fernsehtechnik Datenkompression und Übertragung. Springer, Berlin

    Google Scholar 

  23. Robinson G (2002) Spam detection. http://radio.weblogs.com/0101454/stories/2002/09/16/spamDetection.html

  24. Robinson G (2003) A statistical approach to the spam problem. Linux J 2003(107):3

    Google Scholar 

  25. Robinson G (2004) Handling redundancy in email token probabilities. http://garyrob.blogs.com/handlingtokenredundancy94.pdf

  26. Salembier P, Smith JR (2002) Overview of multimedia description schemes and schema tools. In: Manjuta BS, Salembier P, Sikora T (eds) Introduction to MPEG-7, chap 6. Wiley, Chichester, pp 83–93

    Google Scholar 

  27. Segaran T (2007) Programming collective intelligence: building Smart Web 2.0 applications. O’Reilly, Sebastopol

    Google Scholar 

  28. Stumpf S, Rajaram V, Li L, Burnett M, Dietterich T, Sullivan E, Drummond R, Herlocker J (2007) Toward harnessing user feedback for machine learning. In: IUI ’07: proceedings of the 12th international conference on Intelligent user interfaces. ACM, New York, pp 82–91

    Chapter  Google Scholar 

  29. WeißD, Scheuerer J, Wenleder M, Erk A, Gülbahar M, Linnhoff-Popien C (2008) A user profile-based personalization system for digital multimedia content. In: DIMEA ’08: proceedings of the 3rd international conference on digital interactive media in entertainment and arts. ACM, New York, pp 281–288

    Chapter  Google Scholar 

  30. Zaslow J (2002) If tivo thinks you are gay, here’s how to set it straight. Wall Street J

  31. Zdziarski JA (2005) Ending spam: Bayesian content filtering and the art of statistical language classification. No Starch, San Francisco

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank epgData.com for providing us with their EPG data.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Günther Hölbling.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hölbling, G., Pleschgatternig, M. & Kosch, H. PersonalTV. Multimed Tools Appl 46, 259–288 (2010). https://doi.org/10.1007/s11042-009-0352-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-009-0352-2

Keywords

Navigation