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Found 5 papers, 2 papers with code
Decomposition and Interleaving for Variance Reduction of Post-click Metrics
The proposed method involves (1) the decomposition of the post-click metric measurement of a ranking into a click model estimation and a post-click metric measurement of each item in the ranking, and (2) interleaving of multiple rankings to produce a single ranking that preferentially exposes items possessing a high population variance.
Theoretical Analysis on the Efficiency of Interleaved Comparisons
This study presents a theoretical analysis on the efficiency of interleaving, an efficient online evaluation method for rankings.
The Effect of News Article Quality on Ad Consumption
We conducted a service log analysis and showed that sessions with high-quality news article exposure had more ad consumption than those with low-quality news article exposure.
CS-lol: a Dataset of Viewer Comment with Scene in E-sports Live-streaming
Billions of live-streaming viewers share their opinions on scenes they are watching in real-time and interact with the event, commentators as well as other viewers via text comments.
Greedy Optimized Multileaving for Personalization
We clarify the challenges of applying this method to personalized rankings.
