Automatic association of new items
Information Processing and Management: an International Journal - Special issue on electronic news
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
The Journal of Machine Learning Research
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Evaluation campaigns and TRECVid
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Foundations and Trends in Information Retrieval
Computer
A new approach to cross-modal multimedia retrieval
Proceedings of the international conference on Multimedia
Sampling strategies for bag-of-features image classification
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Real-Time Visual Concept Classification
IEEE Transactions on Multimedia
Proceedings of the 20th ACM international conference on Multimedia
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We investigate the feasibility of training visual concept detectors for such abstract subject categories as biology and history with the aim of employing these for full-text to image linking. We show that using dense sampling methods can lead to image classifiers that perform well enough for interactive search. Echoing this dense sampling in the image domain, we also show that using term frequencies as text features outperforms using a topic abstraction method. Finally, we use these monomodal classifiers for the task of linking texts to images, improving more than 50% over the state-of-the-art, thereby showing that dense is better.