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Title: Multiple Testing for IR and Recommendation System Experiments
While there has been significant research on statistical techniques for comparing two information retrieval (IR) systems, many IR experiments test more than two systems. This can lead to inflated false discoveries due to the multiple-comparison problem (MCP). A few IR studies have investigated multiple comparison procedures; these studies mostly use TREC data and control the familywise error rate. In this study, we extend their investigation to include recommendation system evaluation data as well as multiple comparison procedures that controls for False Discovery Rate (FDR).  more » « less
Award ID(s):
2415042
PAR ID:
10497108
Author(s) / Creator(s):
;
Publisher / Repository:
Springer
Date Published:
Journal Name:
ECIR 2024: Advances in Information Retrieval
Volume:
14610
ISBN:
978-3-031-56063-7
Page Range / eLocation ID:
449-457
Subject(s) / Keyword(s):
recommender systems evaluation statistical inference multiple comparisons
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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