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<oembed><version>1.0</version><provider_name>Glosarix</provider_name><provider_url>https://glosarix.com/en/</provider_url><author_name>Team Glosarix</author_name><author_url>https://glosarix.com/en/author/adm_glosarix/</author_url><title>Relevance Feedback in Multimodal Systems - Glosarix</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="bEsLGBnUM7"&gt;&lt;a href="https://glosarix.com/en/glossary/relevance-feedback-in-multimodal-systems-en/"&gt;Relevance Feedback in Multimodal Systems&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://glosarix.com/en/glossary/relevance-feedback-in-multimodal-systems-en/embed/#?secret=bEsLGBnUM7" width="600" height="338" title="&#x201C;Relevance Feedback in Multimodal Systems&#x201D; &#x2014; Glosarix" data-secret="bEsLGBnUM7" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script&gt;
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</html><description>Description: Relevance feedback in multimodal systems is an approach that integrates user opinions and interactions to optimize the performance of information retrieval systems that handle multiple data modalities, such as text, images, audio, and video. This method allows systems to learn and adapt to the specific preferences and needs of users, thereby improving the accuracy [&hellip;]</description></oembed>
