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2006
ACM

Relevance feedback methods for logo and trademark image retrieval on the web

9 years 1 months ago
Relevance feedback methods for logo and trademark image retrieval on the web
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. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval—Relevance feedback, Query formulation, Retrieval models, Search process General Terms Performance, Experimentation, Algorithms Keywords Image retrieval, Relevance feedback, World Wide Web
Euripides G. M. Petrakis, Klaydios Kontis, Epimeni
Added 14 Jun 2010
Updated 14 Jun 2010
Type Conference
Year 2006
Where SAC
Authors Euripides G. M. Petrakis, Klaydios Kontis, Epimenidis Voutsakis, Evangelos E. Milios
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