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Unsupervised Rank Fusion for Diverse Image Metasearch
2019
Anais do Simpósio Brasileiro de Banco de Dados (SBBD)
For a given query and a set of images ranked lists retrieved from multiple search engines, the metasearch technique aims at combining these lists to build an unified ranking with improved relevance. Rank aggregation is an approach that has been widely used to support this task. This paper investigates the use of rank aggregation methods in the metasearch scenario for diverse image retrieval. Although metasearch systems are usually driven by the relevance of the final result, the impact on
doi:10.5753/sbbd.2019.8834
dblp:conf/sbbd/FigueredoC19
fatcat:z5u7vicnbbforkna4y5xqgs7xu