Please use this identifier to cite or link to this item:
Title: Video reference: Question answering on YouTube
Authors: Li, G. 
Ming, Z. 
Li, H. 
Chua, T.-S. 
Keywords: Video content analysis
Video question answering
Issue Date: 2009
Citation: Li, G.,Ming, Z.,Li, H.,Chua, T.-S. (2009). Video reference: Question answering on YouTube. MM'09 - Proceedings of the 2009 ACM Multimedia Conference, with Co-located Workshops and Symposiums : 773-776. ScholarBank@NUS Repository.
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 direct and intuitive. Currently, there is very little research on automatically presenting precise reference videos based on user's question. In this paper, we explore how to leverage YouTube video collections as a source of reference to fulfilll such task and develop a novel multimedia application named:Video Reference. There are two steps to generating a video reference. The first is recall-driven video search, which is to increase the coverage of question by finding other similar questions. The second is precision-based video ranking. A three level ranking scheme based on visual analysis, opinion analysis and video redundancy is adopted to find the most relevant video reference from YouTube. Experiments conducted using questions from Consumer Electronics domain of Yahoo! Answers archive show the feasibility and effectiveness of our approach. Copyright 2009 ACM.
Source Title: MM'09 - Proceedings of the 2009 ACM Multimedia Conference, with Co-located Workshops and Symposiums
ISBN: 9781605586083
DOI: 10.1145/1631272.1631411
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.