Video reference: a video question answering engine

Authors:
Lei Gao;Guangda Li;Yan-Tao Zheng;Richang Hong;Tat-Seng Chua
Affiliations:
Peking University;National University of Singapore;National University of Singapore;National University of Singapore;National University of Singapore
Venue:
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Year:
2010

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Abstract

Community-based question answering systems have become very popular for providing answers to a wide variety of ”how-to” questions. However, most such systems present only textual answers. In many cases, users would prefer visual answers such as videos which are more intuitive and informative. The Video Reference system is proposed as a solution to the above problem. It automatically extracts videos from YouTube as a video reference responding to a textual question. The demo shows results on real questions sampled from Yahoo! Answering.