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dc.titleExploring large scale data for multimedia QA: An initial study
dc.contributor.authorHong, R.
dc.contributor.authorLi, G.
dc.contributor.authorNie, L.
dc.contributor.authorTang, J.
dc.contributor.authorChua, T.-S.
dc.identifier.citationHong, R.,Li, G.,Nie, L.,Tang, J.,Chua, T.-S. (2010). Exploring large scale data for multimedia QA: An initial study. CIVR 2010 - 2010 ACM International Conference on Image and Video Retrieval : 74-81. ScholarBank@NUS Repository. <a href="" target="_blank"></a>
dc.description.abstractWith the explosive growth of multimedia contents on the internet, multimedia search has become more and more important. However, users are often bewildered by the vast quantity of information content returned by the search engines. In this scenario, Multimedia Question-Answering (MMQA) emerges as a way to return precise answers by leveraging advanced media content and linguistic analysis as well as domain knowledge. This paper performs an initial study on exploring large scale data for MMQA. First, we construct a web video dataset and discuss its query strategy, statistics, feature description and groundtruth. We then conduct experiments based on the dataset to answer definition event questions using three schemes. We finally conclude the study with discussion for future work. © 2010 ACM.
dc.subjectMultimedia Question-Answering
dc.subjectWeb video
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleCIVR 2010 - 2010 ACM International Conference on Image and Video Retrieval
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