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2012 IEEE Conference on Visual Analytics Science and Technology (VAST)

DOI: 10.1109/vast.2012.6400551

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Information retrieval failure analysis: Visual analytics as a support for interactive “what-if” investigation

Proceedings article published in 2012 by Marco Angelini, Nicola Ferro, Guido Granato, Guiseppe Santucci ORCID, Gianmaria Silvello
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

This poster provides an analytical model for examining performances of IR systems, based on the discounted cumulative gain family of metrics, and visualization for interacting and exploring the performances of the system under examination. Moreover, we propose machine learning approach to learn the ranking model of the examined system in order to be able to conduct a "what-if" analysis and visually explore what can happen if you adopt a given solution before having to actually implement it.