Visual information retrieval
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Graph Visualization and Navigation in Information Visualization: A Survey
IEEE Transactions on Visualization and Computer Graphics
Visual structures for image browsing
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
An adaptive technique for content-based image retrieval
Multimedia Tools and Applications
Interactive components for visual exploration of multimedia archives
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
A survey of browsing models for content based image retrieval
Multimedia Tools and Applications
Revisiting IR Techniques for Collaborative Search Strategies
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
An aspectual interface for supporting complex search tasks
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Image classification for content-based indexing
IEEE Transactions on Image Processing
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In this paper, we present a study of adaptive image browsing, based on high-level classification. The underlying hypothesis is that the performance of a browsing model can be improved by integrating high-level semantic concepts. We introduce a multi-label classification model designed to alleviate a binary classification problem in image classification. The effectiveness of this approach is evaluated by using a simulated user evaluation methodology. The results show that the classification assists users to narrow down the search domain and to retrieve more relevant results with respect to less amount of browsing effort.