Abstract
In visual information retrieval, a semantic gap exists due to the poor match between machine-understood content of an information object and the userpercepted one. The mismatch of perception results in di.culties for a user in formulating the query, and consequently in inability for the retrieval system to produce satisfactory answers. Adding searcher’s relevance judgements for (intermediary) search results is known to improve the retrieval. With relevance feedback the system learns the user’s information need through interaction.
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Boldareva, L.V. (2005). Improving Image Representation with Relevance Judgements from the Searchers. In: Losada, D.E., Fernández-Luna, J.M. (eds) Advances in Information Retrieval. ECIR 2005. Lecture Notes in Computer Science, vol 3408. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31865-1_49
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DOI: https://doi.org/10.1007/978-3-540-31865-1_49
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