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Advertising based on users' photos

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

In this paper, we tackle the problem of learning a user's interest from his photo collections and suggesting relevant ads. We address two key challenges in this work: 1) understanding a user's photos to detect his interest, and 2) bridging the lexical and semantic gap between the vocabulary of ads and that of general users' photos. We solve the first problem by employing a data-driven image annotation approach to annotate each photo and modeling a group of photos, and tackle the second problem by learning and matching the topics of users' photos and ads. The experiments based on real Flickr data showed the effectiveness of the approach. ©2009 IEEE.
Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Conference on Multimedia and Expo, ICME 2009
Pages1640-1643
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 IEEE International Conference on Multimedia and Expo, ICME 2009 - New York, NY, United States
Duration: 28 Jun 20093 Jul 2009

Publication series

NameProceedings - 2009 IEEE International Conference on Multimedia and Expo, ICME 2009

Conference

Conference2009 IEEE International Conference on Multimedia and Expo, ICME 2009
PlaceUnited States
CityNew York, NY
Period28/06/093/07/09

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • Image advertising
  • User interest modeling

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