Online training of concept detectors for image retrieval using streaming clickthrough data
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- 作者：Ioannis Sarafis ; sarafis@mug.ee.auth.gr" class="auth_mail" title="E-mail the corresponding author ; Christos Diou diou@mug.ee.auth.gr" class="auth_mail" title="E-mail the corresponding author ; Anastasios Delopoulos adelo@eng.auth.gr" class="auth_mail" title="E-mail the corresponding author
- 关键词：Clickthrough data ; Online learning ; Image retrieval ; Label noise ; Fuzzy SVM ; LASVM
- 刊名：Engineering Applications of Artificial Intelligence
- 出版年：2016
- 出版时间：May 2016
- 年：2016
- 卷：51
- 期：Complete
- 页码：150-162
- 全文大小：2928 K
文摘
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Online training of concept detectors on streaming clickthrough data for image retrieval.
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Continuous model update based on the stream of incoming clicks.
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Implicit importance weighting of training samples based on the number of clicks.
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Online concept detectors demonstrate high effectiveness and noise robustness.
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Sample selection strategies boost the performance and speedup convergence.