Creation of Reliable Relevance Judgments in Information Retrieval Systems Evaluation Experimentation through Crowdsourcing: A Review

Author:

Samimi Parnia1,Ravana Sri Devi1

Affiliation:

1. Department of Information Systems, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia

Abstract

Test collection is used to evaluate the information retrieval systems in laboratory-based evaluation experimentation. In a classic setting, generating relevance judgments involves human assessors and is a costly and time consuming task. Researchers and practitioners are still being challenged in performing reliable and low-cost evaluation of retrieval systems. Crowdsourcing as a novel method of data acquisition is broadly used in many research fields. It has been proven that crowdsourcing is an inexpensive and quick solution as well as a reliable alternative for creating relevance judgments. One of the crowdsourcing applications in IR is to judge relevancy of query document pair. In order to have a successful crowdsourcing experiment, the relevance judgment tasks should be designed precisely to emphasize quality control. This paper is intended to explore different factors that have an influence on the accuracy of relevance judgments accomplished by workers and how to intensify the reliability of judgments in crowdsourcing experiment.

Funder

Universiti Malaya

Publisher

Hindawi Limited

Subject

General Environmental Science,General Biochemistry, Genetics and Molecular Biology,General Medicine

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Assessment of the Nursing Observatory as a support tool to combat the contamination of nursing professionals by COVID;Proceedings of the 16th International Conference on Theory and Practice of Electronic Governance;2023-09-26

2. Relevance Judgment Convergence Degree—A Measure of Assessors Inconsistency for Information Retrieval Datasets;Lecture Notes in Information Systems and Organisation;2023

3. Wolaytta-English Cross-lingual Information Retrieval using Neural Machine Translation;2022 International Conference on Information and Communication Technology for Development for Africa (ICT4DA);2022-11-28

4. Relevance Judgment Convergence Degree – A Measure of Inconsistency among Assessors for Information Retrieval;International Conference on Information Systems Development;2022-09-19

5. The HoPE Model Architecture: a Novel Approach to Pregnancy Information Retrieval Based on Conversational Agents;Journal of Healthcare Informatics Research;2022-04-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3