Visual Comparison of Ranked Result Cumulated Gains

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dc.contributor.authorFerro, N.en_US
dc.contributor.authorSabetta, A.en_US
dc.contributor.authorSantucci, G.en_US
dc.contributor.authorTino, G.en_US
dc.contributor.authorVeltri, F.en_US
dc.contributor.editorSilvia Miksch and Giuseppe Santuccien_US
dc.date.accessioned2014-01-27T15:55:55Z
dc.date.available2014-01-27T15:55:55Z
dc.date.issued2011en_US
dc.description.abstractRanking is fundamental in Information Retrieval (IR) and several measures have been developed over the years to assess the quality of a ranked result list, such as those based on the idea of computing the cumulative gain up to a given ranked position and taking into account multiple relevance levels. These measures allow for comparing the performances of different Information Retrieval System (IRS), giving credit to their ability to retrieve highly relevant documents and to rank them topmost in the result list. However, while this approach is able to assess the differences among two or more retrieval systems, it does not allow to easily understand and inspect the reasons of good or bad performances. To this end, this paper presents a Visual Analytics (VA) environment that allows for visually exploring the ranked retrieval results, pointing out the search failures and providing useful insights for improving the underlying IRS ranking algorithm.en_US
dc.description.seriesinformationEuroVA 2011: International Workshop on Visual Analyticsen_US
dc.identifier.isbn978-3-905673-82-1en_US
dc.identifier.urihttps://doi.org/10.2312/PE/EuroVAST/EuroVA11/021-024en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): H.3.3 [INFORMATION STORAGE AND RETRIEVAL]: Information Search and Retrieval-Search process; H.3.4 [INFORMATION STORAGE AND RETRIEVAL]: Systems and Software-Performance evaluation (efficiency and effectiveness)en_US
dc.titleVisual Comparison of Ranked Result Cumulated Gainsen_US
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