  This paper proposes a theoretical framework which models the information
provided by retrieval systems in terms of Information Theory. The proposed
framework allows to formalize: (i) system effectiveness as an information
theoretic similarity between system outputs and human assessments, and (ii)
ranking fusion as an information quantity measure. As a result, the proposed
effectiveness metric improves popular metrics in terms of formal constraints.
In addition, our empirical experiments suggest that it captures quality aspects
from traditional metrics, while the reverse is not true. Our work also advances
the understanding of theoretical foundations of the empirically known
phenomenon of effectiveness increase when combining retrieval system outputs in
an unsupervised manner.
