Presentation at WWW’09

Yesterday it was my turn for presenting our full-paper accepted into this year edition of ACM World Wide Web conference (WWW’09). The expectation for the “Photos and Web 2.0” session was far beyond the calculations of the organizers, and the room allocated for the talks was simply too small for all the people that showed up. Many had to see the first presentation of the session looking through the door while standing in the corridor. It was during the second presentation (my one) that they decided to remove the panels at the rear to merge with an empty room just behind. Though it was absolutely necessary I simply do not understand why they decided to do it right in the middle of my talk. I loss my concentration completely and it was difficult to re-start the talk again.
Despite the difficulties, the presentation went alright and it lead to a positive reaction from the audience which asked a good amount of interesting questions. The slides are available from the www2009 epapers website.

See you in Boston next July! Sigir awaits!

Full paper accepted into SIGIR’09!

My submission to SIGIR 2009 has been accepted as a full paper. The article, entitled “Automatic Video Tagging using Content Redundancy”, proposes an interesting approach to the exploitation of redundant content in folksonomies. We consider the specific case of the leading video sharing website, YouTube. CBCR techniques are used to automatically detect duplication in the video collection, and several metadata propagation methods are proposed to spread community knowledge around the graph of resources.

The abstract of the paper follows below:

“The analysis of the leading social video sharing platform YouTube reveals a high amount of redundancy, in the form of videos with overlapping or duplicated content. In this paper, we show that this redundancy can provide useful information about connections between videos. We reveal these links using robust content-based video analysis techniques and exploit them for generating new tag assignments. To this end, we propose different tag propagation methods for automatically obtaining richer video annotations. Our techniques provide the user with additional information about videos, and lead to enhanced feature representations for applications such as automatic data organization and search. Experiments on video clustering and classification as well as a user evaluation demonstrate the viability of our approach.”