Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
SVM Classification Using Sequences of Phonemes and Syllables
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Support vector machines for spam categorization
IEEE Transactions on Neural Networks
Video classification as IR task: experiments and observations
CLEF'09 Proceedings of the 10th international conference on Cross-language evaluation forum: multimedia experiments
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The VideoCLEF 2008 Vid2RSS task involves the assignment of thematic category labels to dual language (Dutch/English) television episode videos. The University of Amsterdam chose to focus on exploiting archival metadata and speech transcripts generated by both Dutch and English speech recognizers. A Support Vector Machine (SVM) classifier was trained on training data collected from Wikipedia. The results provide evidence that combining archival metadata with speech transcripts can improve classification performance, but that adding speech transcripts in an additional language does not yield performance gains.