2012 KeywordPropagationbasedInformat

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The volume of Web videos have increased sharply through the past several years because of the evolvement of Web video sites.Enhanced algorithms on retrieval, classification and TDT (abbreviation of Topic Detection and Tracking) can bring lots of convenience to Web users as well as release tedious work from the administrators. Nevertheless, due to the the insufficiency of annotation keywords and the gap between video features and semantic concepts, it is still far away from satisfactory to implement them based on initial keywords and visual features. In this paper we utilize a keyword propagation algorithm based on manifold structure to enrich the keyword information and remove the noise for videos. Both text similarity and temporal similarity are employed to explore the relationship between any pair of videos and to construct the propagation model. We explore three applications, i.e., TDT, Retrieval and Classification based on a Web news video dataset obtained from a famous online video-distributing website, YouKu, and evaluate our approach. Experimental results demonstrate that they achieve satisfactory performance and always outperform the baseline methods.



 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2012 KeywordPropagationbasedInformatJun Zhang
Xiaoming Fan
Jianyong Wang
Lizhu Zhou
Keyword-propagation-based Information Enriching and Noise Removal for Web News Videos10.1145/2339530.23396202012