Search Results for author:
Found 5 papers, 5 papers with code
On the Impact of Outlier Bias on User Clicks
We therefore propose an outlier-aware click model that accounts for both outlier and position bias, called outlier-aware position-based model ( OPBM).
Fairness of Exposure in Light of Incomplete Exposure Estimation
In this work, we discuss how to approach fairness of exposure in cases where the policy contains rankings of which, due to inter-item dependencies, we cannot reliably estimate the exposure distribution.
Probabilistic Permutation Graph Search: Black-Box Optimization for Fairness in Ranking
Different from PL, where pointwise logits are used as the distribution parameters, in PPG pairwise inversion probabilities together with a reference permutation construct the distribution.
Understanding and Mitigating the Effect of Outliers in Fair Ranking
We formalize outlierness in a ranking, show that outliers are present in realistic datasets, and present the results of an eye-tracking study, showing that users scanning order and the exposure of items are influenced by the presence of outliers.
A Comparison of Supervised Learning to Match Methods for Product Search
As recent learning to match methods have made important advances in bridging the vocabulary gap for these traditional IR areas, we investigate their potential in the context of product search.
