Many evaluation metrics have been defined to evaluate the effectiveness
ad-hoc retrieval and search result diversification systems. However, it is
often unclear which evaluation metric should be used to analyze the performance
of retrieval systems given a specific task. Axiomatic analysis is an
informative mechanism to understand the fundamentals of metrics and their
suitability for particular scenarios. In this paper, we define a
constraint-based axiomatic framework to study the suitability of existing
metrics in search result diversification scenarios. The analysis informed the
definition of Rank-Biased Utility (RBU) -- an adaptation of the well-known
Rank-Biased Precision metric -- that takes into account redundancy and the user
effort associated to the inspection of documents in the ranking. Our
experiments over standard diversity evaluation campaigns show that the proposed
metric captures quality criteria reflected by different metrics, being suitable
in the absence of knowledge about particular features of the scenario under
study.Comment: Original version: 10 pages. Preprint of full paper to appear at
SIGIR'18: The 41st International ACM SIGIR Conference on Research &
Development in Information Retrieval, July 8-12, 2018, Ann Arbor, MI, USA.
ACM, New York, NY, US