A Visual Analytics Tool for Experimental Evaluation

Information Retrieval is a research field strongly rooted in experimentation. Indeed, measuring is a key to scientific progress. Multilingual and multimedia information access systems, such as search engines, are increasingly complex: they need to satisfy diverse user needs and support challenging tasks. It is therefore fundamental to provide automated tools to examine system behaviour, both visually and analytically. This paper 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.