With the emergence of various information access systems exhibiting increasing complexity,
there is a critical need for sound and scalable means of automatic evaluation. To address …

In this work, we define and solve the Fair Top-k Ranking problem, in which we want to
determine a subset of k candidates from a large pool of n» k candidates, maximizing utility …

We introduce the concept of expected exposure as the average attention ranked items
receive from users over repeated samples of the same query. Furthermore, we advocate for …

Ranking items or people is a fundamental operation at the basis of several processes and
services, not all of them happening online. Ranking is required for different tasks, including …

Relevance is a fundamental concept in information retrieval (IR) studies. It is however often
observed that relevance as annotated by secondary assessors may not necessarily mean …

Diversifying return results is an important research topic in retrieval systems in order to
satisfy both the various interests of customers and the equal market exposure of providers …

Recommender systems evaluation has evolved rapidly in recent years. However, for offline
evaluation, accuracy is the de facto standard for assessing the superiority of one method …

Document ranking is one of the most studied but challenging problems in information
retrieval (IR) research. A number of existing document ranking models capture relevance …

A large percentage of queries issued to search engines are broad or ambiguous. Search
result diversification aims to solve this problem, by returning diverse results that can fulfill as …

This study evaluates 30 IR evaluation measures or their instances, of which nine are for
adhoc IR and 21 are for diversified IR, primarily from the viewpoint of whether their …