Classifying tags using open content resources
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Understanding user's query intent with wikipedia
Proceedings of the 18th international conference on World wide web
Automatic video tagging using content redundancy
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Towards google challenge: combining contextual and social information for web video categorization
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Labeling News Topic Threads with Wikipedia Entries
ISM '09 Proceedings of the 2009 11th IEEE International Symposium on Multimedia
Context-oriented web video tag recommendation
Proceedings of the 19th international conference on World wide web
On the Annotation of Web Videos by Efficient Near-Duplicate Search
IEEE Transactions on Multimedia
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This paper presents a novel approach for web video categorization by leveraging Wikipedia categories (WikiCs) and open resources describing the same content as the video, i.e., content-duplicated open resources (CDORs). Note that current approaches only collect CDORs within one or a few media forms and ignore CDORs of other forms. We explore all these resources by utilizing WikiCs and commercial search engines. Given a web video, its discriminative Wikipedia concepts are first identified and classified. Then a textual query is constructed and from which CDORs are collected. Based on these CDORs, we propose to categorize web videos in the space spanned by WikiCs rather than that spanned by raw tags. Experimental results demonstrate the effectiveness of both the proposed CDOR collection method and the WikiC voting categorization algorithm. In addition, the categorization model built based on both WikiCs and CDORs achieves better performance compared with the models built based on only one of them as well as state-of-the-art approach.