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invited-talk

Personalized Catch-up & DVR: VOD or Linear, That is the Question

Published: 16 September 2015 Publication History

Abstract

The expansion of TV services such as DVR and, more recently, Catch-up have removed the temporal constraint typical of the Linear "appointment" TV enabling users to watch content they love at any time and on-demand. However, the DVR and Catch-up TV libraries, while providing a convenient time-shifted "on-demand" consumption, are indeed composed by content recently aired on a linear channel, so that they have more in common with Linear TV than they have with VOD. In this talk we will present and discuss the main challenges and some possible solutions to personalize the user experience with content from DVR and Catch-up TV, such as: (i) The consumption pattern is strongly affected by the context (e.g., time and device used to access the video service). (ii) Some content is consumed serially and still follows seasonal dynamics (e.g., TV Series). (iii) The system is fed with a massive and very dynamic streams of data (e.g., new content arriving right after broadcast, signals of user interactions). (iv) The same piece of content may coexist across multiple services provided by the same operator (e.g., linear schedule, network-DVR, catch-up TV, subscription VOD, rental VOD).

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Published In

cover image ACM Conferences
RecSys '15: Proceedings of the 9th ACM Conference on Recommender Systems
September 2015
414 pages
ISBN:9781450336925
DOI:10.1145/2792838
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 September 2015

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Author Tags

  1. DVR
  2. TV
  3. VOD
  4. catch-up
  5. content lifecycle
  6. context
  7. linear TV
  8. personalization
  9. predictive analytics
  10. recommender systems
  11. video on demand

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  • Invited-talk

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RecSys '15
Sponsor:
RecSys '15: Ninth ACM Conference on Recommender Systems
September 16 - 20, 2015
Vienna, Austria

Acceptance Rates

RecSys '15 Paper Acceptance Rate 28 of 131 submissions, 21%;
Overall Acceptance Rate 254 of 1,295 submissions, 20%

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