QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees
Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto and Rossano Venturini
For a paper that develops a novel representation of binary regression trees based on bitvectors and an algorithm to perform a fast interleaved traversal of the trees in a cache-aware fashion, and demonstrates significant efficiency gains on publically available learning-to-rank data sets with various models that use ensembles of regression trees.
Sequential Testing for Early Stopping of Online Experiments
Eugene Kharitonov, Aleksandr Vorobev, Craig Macdonald, Pavel Serdyukov, Iadh Ounis
For a paper that extends sequential statistical testing procedures by adjusting stopping thresholds based on observed log data, and demonstrates how this significantly reduce the time required for online A/B and interleaving experiments.
The Benefits of Magnitude Estimation for Relevance Assessment
Eddy Maddalena, Stefano Mizzaro, Falk Scholer and Andrew Turpin
An Eye-Tracking Study of Query Reformulation
Carsten Eickhoff, Sebastian Dungs and Vu Tran
Incorporating Non-sequential Behavior into Click Models
Chao Wang, Yiqun Liu, Meng Wang, Ke Zhou, Jian-Yun Nie and Shaoping Ma