1 / 20

The future of Media Personalization

The future of Media Personalization. Agenda. Customization and personalization aspects: Place (home, mobile) Time Content Personalization/Recommendation engines Intro to media recommendation methods Media personalization in IPTV, Mobile and Web Personalization in advertisement - Targeting

vesna
Download Presentation

The future of Media Personalization

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. The future of Media Personalization

  2. Agenda • Customization and personalization aspects: • Place (home, mobile) • Time • Content • Personalization/Recommendation engines • Intro to media recommendation methods • Media personalization in IPTV, Mobile and Web • Personalization in advertisement - Targeting • Personalized video Ads on mobile & Web • Seambi example

  3. Media Customization Place adaptation • Place • Time • Content type • This lecture concentrate on how to adapt/personalize the content. VOD PVR Broadcast TV PC Owned content UGC Mobile Personalized content Time adaptation Content Type adaptation

  4. Content personalization • There is a surge in the amount of available content: • 1 channel -> Thousands of channels • 10 VoD Titles->Thousands of VoD titles • Tens of millions of UGC clips • How to select the right content? • Let the system select the content for you Media Recommendation Engines

  5. Why Recommendation Engine?

  6. Recommendation Engine Methods Technology is mostly: natural language processing Correlation matrix Source: TrustedOpinion

  7. Music Recommendation Services

  8. MeeMix • Analyze the user taste in order to provide the best personalized music channel

  9. Video Recommendation samples • Commercial version of MovieLens with better features & GUI Collaborative /Peer based Content based

  10. Desktop/web application sample • Recommendation/Rating: • Based on the known 1-5 star system • Use of peer/group recommendation icon

  11. Mobile sample • Rating is kept simple: • Like it/hate it/no opinion • Recommend ions are: • You’ll love it • You might love it

  12. Movie selection ->personal channels • Once we are sure of users needs we can assist him in creating his own “Personal TV Channel” • Personal channel is most common in: • Music Recommendation Engine • Mobile recommendation engine • Starting to catch up on Web TV channels • Channel Creation Platforms

  13. Trends

  14. Trends • Recommendation Systems closes the loop between content creator/distributers and the users

  15. Recommendation engines in Video Advertisement

  16. Advertisement Personalization-Targeting • In broadcast TV ->broadcast Ads • In IPTV and Web we can use flash->video advertisement without transcoding. • Use targeting and peronalization engine • Advertisers use viewers information for ad targeting including: • Location • Demographic • User profile • User content

  17. Personalized Video Ads • Adobe Flash and Microsoft Silverlight Enables: • Using one video version • Changing the video advertisement per user without transcoding the video

  18. Video Advertisement - Standard • Pre and Post Roll • Overly Doomsday Movie advertisement as Overlay on a pre-roll of Doomsday video

  19. Samples of Personalized AD

  20. Thank You !

More Related