By Topic

Online Scheduling of Targeted Advertisements for IPTV

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Kodialam, M. ; Bell Labs., Alcatel-Lucent, Murray Hill, NJ, USA ; Lakshman, T.V. ; Mukherjee, S. ; Limin Wang

Behavioral targeting of content to users is a huge and lucrative business, valued as a $20 billion industry that is growing rapidly. So far, the dominant players in this field like Google and Yahoo! examine the user requests coming to their servers and place appropriate ads based on the user's search keywords. Triple-play service providers have access to all the traffic generated by the users and can generate more comprehensive profiles of users based on their TV, broadband, and mobile usage. Using such multisource profile information, they can generate new revenue streams by smart targeting of ads to their users over multiple screens (computer, TV, and mobile handset). This paper proposes methods to place targeted ads to a TV based on user's interests. It proposes an ad auction model that can leverage multisource profile and can handle dynamic profile-based targeting like Google's AdWords vis-à-vis static demography-based targeting of legacy TV. We then present a 0.502-competitive revenue maximizing scheduling algorithm that chooses a set of ads in each time slot and assigns users to one of these selected ads.

Published in:

Networking, IEEE/ACM Transactions on  (Volume:19 ,  Issue: 6 )