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dc.contributor.authorAngelini, Marcoen_US
dc.contributor.authorFerro, Nicolaen_US
dc.contributor.authorSantucci, Giuseppeen_US
dc.contributor.authorSilvello, Gianmariaen_US
dc.contributor.editorMichael Sedlmair and Christian Tominskien_US
dc.date.accessioned2017-06-12T05:16:25Z
dc.date.available2017-06-12T05:16:25Z
dc.date.issued2017
dc.identifier.isbn978-3-03868-042-0
dc.identifier.urihttp://dx.doi.org/10.2312/eurova.20171115
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurova20171115
dc.description.abstractInformation Retrieval (IR) has been deeply rooted in experimentation since its inception, allowing researchers and developers to understand the behavior and interactions within increasingly complex IR systems, such as web search engines, which have to address ever increasing user needs and support challenging tasks. This paper focuses on the innovative Visual Analytics (VA) approach realized by the Participative Research labOratory for Multimedia and Multilingual Information Systems Evaluation (PROMISE) environment, which simplifies and makes more effective the experimental evaluation process by allowing a formal and structured way to explore the complex data set of measures produced along an evaluation campaign. The system uses the result produced within the Conference and Labs of the Evaluation Forum (CLEF) [Cle].en_US
dc.publisherThe Eurographics Associationen_US
dc.titleVisual Analytics for Information Retrieval Evaluation Campaignsen_US
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)
dc.description.sectionheadersSensemaking, Analytics, and Retrieval
dc.identifier.doi10.2312/eurova.20171115
dc.identifier.pages25-29


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