Skip to main content

Research Repository

Advanced Search

Query performance prediction and effectiveness evaluation without relevance judgments: Two sides of the same coin

Mizzaro, Stefano; Mothe, Josiane; Roitero, Kevin; Ullah, Md Zia

Authors

Stefano Mizzaro

Josiane Mothe

Kevin Roitero



Abstract

Some methods have been developed for automatic effectiveness evaluation without relevance judgments. We propose to use those methods, and their combination based on a machine learning approach, for query performance prediction. Moreover, since predicting average precision as it is usually done in query performance prediction literature is sensitive to the reference system that is chosen, we focus on predicting the average of average precision values over several systems. Results of an extensive experimental evaluation on ten TREC collections show that our proposed methods outperform state-of-the-art query performance predictors.

Presentation Conference Type Conference Paper (Published)
Conference Name SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval
Start Date Jul 8, 2018
End Date Jul 12, 2018
Online Publication Date Jun 27, 2018
Publication Date 2018-06
Deposit Date Mar 13, 2023
Publisher Association for Computing Machinery (ACM)
Pages 1233-1236
Book Title SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval
ISBN 9781450356572
DOI https://doi.org/10.1145/3209978.3210146