/* ---- Google Analytics Code Below */

Saturday, October 29, 2022

Fairer Search Results

 Ranking, Fairness. 

Fairer Ranking System Diversifies Search Results

Cornell Chronicle

Patricia Waldron,  September 19, 2022

Cornell University researchers Yuta Saito and Thorsten Joachims have developed a fairer ranking system for recommendations that prevents search results from only highlighting a few top hits. Conventional recommender systems try ranking items based on what users want to see, so Saito designed the enhanced ranking system according to the economic principles of "fair division." The researchers used synthetic and real-world data to test the system's feasibility. The system returns viable results that rank items' benefits better than random discovery, does not easily improve items' impact, and does not confer an advantage to any item by switching how it is ranked versus other items in a series of searches. Saito said the framework "can be applied to any type of two-sided ranking system."

No comments: