@inproceedings{8e266ceb659d4b6298cb3d7755a33f80,
title = "Query Performance Prediction Using a Child-Focused Definition of Relevance",
abstract = "Query performance prediction (QPP) methods have primarily been tailored to mainstream users, thus relying on the traditional concept of relevance. In the case of children, however, relevance goes beyond content-based resource-query matching, which is why we gauge the performance of existing QPP methods in estimating the fit of resources retrieved in response to child-formulated queries. Outcomes from our empirical exploration of various QPP methods using a traditional and a child-focused definition of relevance on 2 datasets reveal the limitations in the adaptability of existing methods to the context of child information retrieval.",
keywords = "Children, Query Performance Prediction",
author = "Hrishita Chakrabarti and Pera, \{Maria Soledad\}",
year = "2026",
doi = "10.1007/978-3-032-21300-6\_29",
language = "English",
isbn = "9783032212993",
series = "Lecture Notes in Computer Science",
publisher = "Springer Nature",
pages = "388--399",
editor = "Ricardo Campos and Adam Jatowt and Yanyan Lan and Mohammad Aliannejadi and Christine Bauer and Sean MacAvaney and Avishek Anand and Nan Bai and Masoud Mansoury and Zhaochun Ren and Suzan Verberne",
booktitle = "Advances in Information Retrieval - 48th European Conference on Information Retrieval, ECIR 2026, Proceedings",
note = "48th European Conference on Information Retrieval, ECIR 2026 ; Conference date: 29-03-2026 Through 02-04-2026",
}