Content-based image retrieval using a composite color-shape approach
Information Processing and Management: an International Journal
The connectivity server: fast access to linkage information on the Web
WWW7 Proceedings of the seventh international conference on World Wide Web 7
A unified framework for semantics and feature based relevance feedback in image retrieval systems
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Web mining for web image retrieval
Journal of the American Society for Information Science and Technology - Visual based retrieval systems and web mining
MindReader: Querying Databases Through Multiple Examples
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
FALCON: Feedback Adaptive Loop for Content-Based Retrieval
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Image Retrieval from the World Wide Web: Issues, Techniques, and Systems
ACM Computing Surveys (CSUR)
Weighted Link Analysis for Logo and Trademark Image Retrieval on the Web
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
A hybrid ontology and visual-based retrieval model for cultural heritage multimedia collections
International Journal of Metadata, Semantics and Ontologies
Style and branding elements extraction from businessweb sites
Proceedings of the 10th ACM symposium on Document engineering
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Relevance feedback is the state-of-the-art approach for adjusting query results to the needs of the users. This work extends the existing framework of image retrieval with relevance feedback on the Web by incorporating text and image content into the search and feedback process. Some of the most powerful relevance feedback methods are implemented and tested on a fully automated Web retrieval system with more than 250,000 logo and trademark images. This evaluation demonstrates that term re-weighting based on text and image content is the most effective approach.