The strategy for selecting candidate sets – the set of items that the
re...
There has been significant research in the last five years on ensuring t...
Current practice for evaluating recommender systems typically focuses on...
A number of information retrieval studies have been done to assess which...
Users of search systems often reformulate their queries by adding query ...
The TREC Fair Ranking Track aims to provide a platform for participants ...
The TREC Fair Ranking Track aims to provide a platform for participants ...
Information access research (and development) sometimes makes use of gen...
The last several years have brought a growing body of work on ensuring t...
Search engines in e-commerce settings allow users to search, browse, and...
Recommender systems research is concerned with many aspects of recommend...
This paper calls attention to the missing component of the recommender s...
This paper provides an overview of the NIST TREC 2020 Fair Ranking track...
In this position paper, we argue for the need to investigate if and how
...
Recommendation, information retrieval, and other information access syst...
Ranking is a fundamental aspect of recommender systems. However, ranked
...
We introduce the concept of expected exposure as the average attention r...
The goal of the TREC Fair Ranking track was to develop a benchmark for
e...
Offline evaluations of recommender systems attempt to estimate users'
sa...
The proceedings list for the program of FACTS-IR 2019, the Workshop on
F...
As the field of recommender systems has developed, authors have used a m...
Since 2010, we have built and maintained LensKit, an open-source toolkit...
Collaborative filtering algorithms find useful patterns in rating and
co...