Metrics, user models, and satisfaction

Abstract

User satisfaction is an important factor when evaluating search systems, and hence a good metric should give rise to scores that have a strong positive correlation with user satisfaction ratings. A metric should also correspond to a plausible user model, and hence provide a tangible manifestation of how users interact with search rankings. Recent work has focused on metrics whose user models accurately portray the behavior of search engine users. Here we investigate whether those same metrics then also correlate with user satisfaction. We carry out experiments using various classes of metrics, and confirm through the lens of the C/W/L framework that the metrics with user models that reflect typical behavior also tend to be the metrics that correlate well with user satisfaction ratings.