Abstract
We propose a relative relevance feedback method for image retrieval systems. Relevance feedback is an effective method to modify a user's query by selecting relevant and irrelevant items in the search result. However, users cannot always find exactly relevant items in the first few search result pages, especially when the initial query is not specified due to the lack of user's knowledge. Thus, we propose relative relevance feedback in the present paper, which allows users to select relatively relevant and irrelevant items, and modifies a query by taking into account the relativity of user's feedback. Our experimental result shows that the relative relevance feedback outperforms a conventional relevance feedback for image retrieval tasks.
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