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Found 9 papers, 0 papers with code
Unified Browsing Models for Linear and Grid Layouts
These metrics take user browsing behavior into account in their measurement strategies to estimate the attention the user is likely to provide to each item in ranking.
Towards Measuring Fairness in Grid Layout in Recommender Systems
We examine how fairness scores change with different ranking layouts to yield insights into (1) the consistency of fair ranking measurements across layouts; (2) whether rankings optimized for fairness in a linear ranking remain fair when the results are displayed in a grid; and (3) the impact of column reduction approaches to support different device geometries on fairness measurement.
Patterns of gender-specializing query reformulation
There are many ways a query, the search results, and a demographic attribute such as gender may relate, leading us to hypothesize different causes for these reformulation patterns, such as under-representation on the original result page or based on the linguistic theory of markedness.
Overview of the TREC 2021 Fair Ranking Track
The 2021 Fair Ranking track aimed to ensure that documents that are about, or somehow represent, certain protected characteristics receive a fair exposure to the Wikipedia editors, so that the documents have an fair opportunity of being improved and, therefore, be well-represented in Wikipedia.
Overview of the TREC 2022 Fair Ranking Track
The 2022 Fair Ranking track aimed to ensure that documents that are about, or somehow represent, certain protected characteristics receive a fair exposure to the Wikipedia editors, so that the documents have an fair opportunity of being improved and, therefore, be well-represented in Wikipedia.
Much Ado About Gender: Current Practices and Future Recommendations for Appropriate Gender-Aware Information Access
Information access research (and development) sometimes makes use of gender, whether to report on the demographics of participants in a user study, as inputs to personalized results or recommendations, or to make systems gender-fair, amongst other purposes.
Fire Dragon and Unicorn Princess; Gender Stereotypes and Children's Products in Search Engine Responses
Search engines in e-commerce settings allow users to search, browse, and select items from a wide range of products available online including children's items.
Pink for Princesses, Blue for Superheroes: The Need to Examine Gender Stereotypes in Kid's Products in Search and Recommendations
In this position paper, we argue for the need to investigate if and how gender stereotypes manifest in search and recommender systems. As a starting point, we particularly focus on how these systems may propagate and reinforce gender stereotypes through their results in learning environments, a context where teachers and children in their formative stage regularly interact with these systems.
Comparing Fair Ranking Metrics
Ranked lists are frequently used by information retrieval (IR) systems to present results believed to be relevant to the users information need.
