- (Zhang et al., 2012) ⇒ Jun Zhang, Xiaoming Fan, Jianyong Wang, and Lizhu Zhou. (2012). “Keyword-propagation-based Information Enriching and Noise Removal for Web News Videos.” In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2012). ISBN:978-1-4503-1462-6 doi:10.1145/2339530.2339620
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.
|2012 KeywordPropagationbasedInformat||Jun Zhang|
|Keyword-propagation-based Information Enriching and Noise Removal for Web News Videos||10.1145/2339530.2339620||2012|
|Author||Jun Zhang +, Xiaoming Fan +, Jianyong Wang + and Lizhu Zhou +|
|proceedings||Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining +|
|title||Keyword-propagation-based Information Enriching and Noise Removal for Web News Videos +|