Word association norms, mutual information, and lexicography
Computational Linguistics
Automated learning of decision rules for text categorization
ACM Transactions on Information Systems (TOIS)
Automatic recognition of film genres
Proceedings of the third ACM international conference on Multimedia
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Journal of Intelligent Information Systems
News video classification using SVM-based multimodal classifiers and combination strategies
Proceedings of the tenth ACM international conference on Multimedia
Normalization in Support Vector Machines
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
Automatic Genre Identification for Content-Based Video Categorization
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Learning the Kernel Matrix with Semidefinite Programming
The Journal of Machine Learning Research
Multiple kernel learning, conic duality, and the SMO algorithm
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Joint categorization of queries and clips for web-based video search
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Semantic Kernels for Text Classification Based on Topological Measures of Feature Similarity
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Multi-modality web video categorization
Proceedings of the international workshop on Workshop on multimedia information retrieval
Structure and semantics for expressive text kernels
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Building semantic kernels for text classification using wikipedia
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient convolution kernels for dependency and constituent syntactic trees
ECML'06 Proceedings of the 17th European conference on Machine Learning
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Improved video categorization from text metadata and user comments
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
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With the explosive growth of online videos, automatic real-time categorization of Web videos plays a key role for organizing, browsing and retrieving the huge amount of videos on the Web. Previous work shows that, in addition to text features, content features of videos are also useful for Web video classification. Unfortunately, extracting content features is computationally prohibitive for real-time video classification. In this paper we propose a novel video classification framework that is able to exploit both content and text features for video classification while avoiding the expensive computation of extracting content features at classification time. The main idea of our approach is to utilize the content features extracted from training data to enrich the text based semantic kernels, yielding content-enriched semantic kernels. The content-enriched semantic kernels enable to utilize both content and text features for classifying new videos without extracting their content features. The experimental results show that our approach significantly outperforms the state-of-the-art video classification methods.