Abstract
In order to satisfy diverse user needs and support challenging tasks, it is fundamental to provide automated tools to examine system behavior, both visually and analytically. This paper provides an analytical model for examining rankings produced by IR systems, based on the discounted cumulative gain family of metrics, and visualization for performing failure and “what-if” analyses.
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Angelini, M., Ferro, N., Santucci, G., Silvello, G. (2013). Improving Ranking Evaluation Employing Visual Analytics. In: Forner, P., Müller, H., Paredes, R., Rosso, P., Stein, B. (eds) Information Access Evaluation. Multilinguality, Multimodality, and Visualization. CLEF 2013. Lecture Notes in Computer Science, vol 8138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40802-1_4
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DOI: https://doi.org/10.1007/978-3-642-40802-1_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40801-4
Online ISBN: 978-3-642-40802-1
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