cwl_eval: An Evaluation Tool for Information Retrieval

L. Azzopardi, Paul Thomas, Alistair Moffat
{"title":"cwl_eval: An Evaluation Tool for Information Retrieval","authors":"L. Azzopardi, Paul Thomas, Alistair Moffat","doi":"10.1145/3331184.3331398","DOIUrl":null,"url":null,"abstract":"We present a tool (\"cwl_eval\") which unifies many metrics typically used to evaluate information retrieval systems using test collections. In the CWL framework metrics are specified via a single function which can be used to derive a number of related measurements: Expected Utility per item, Expected Total Utility, Expected Cost per item, Expected Total Cost, and Expected Depth. The CWL framework brings together several independent approaches for measuring the quality of a ranked list, and provides a coherent user model-based framework for developing measures based on utility (gain) and cost. Here we outline the CWL measurement framework; describe the cwl_eval architecture; and provide examples of how to use it. We provide implementations of a number of recent metrics, including Time Biased Gain, U-Measure, Bejewelled Measure, and the Information Foraging Based Measure, as well as previous metrics such as Precision, Average Precision, Discounted Cumulative Gain, Rank-Biased Precision, and INST. By providing state-of-the-art and traditional metrics within the same framework, we promote a standardised approach to evaluating search effectiveness.","PeriodicalId":20700,"journal":{"name":"Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3331184.3331398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22

Abstract

We present a tool ("cwl_eval") which unifies many metrics typically used to evaluate information retrieval systems using test collections. In the CWL framework metrics are specified via a single function which can be used to derive a number of related measurements: Expected Utility per item, Expected Total Utility, Expected Cost per item, Expected Total Cost, and Expected Depth. The CWL framework brings together several independent approaches for measuring the quality of a ranked list, and provides a coherent user model-based framework for developing measures based on utility (gain) and cost. Here we outline the CWL measurement framework; describe the cwl_eval architecture; and provide examples of how to use it. We provide implementations of a number of recent metrics, including Time Biased Gain, U-Measure, Bejewelled Measure, and the Information Foraging Based Measure, as well as previous metrics such as Precision, Average Precision, Discounted Cumulative Gain, Rank-Biased Precision, and INST. By providing state-of-the-art and traditional metrics within the same framework, we promote a standardised approach to evaluating search effectiveness.
cwl_eval:一个信息检索的评估工具
我们提出了一个工具(“cwl_eval”),它统一了许多通常用于使用测试集合评估信息检索系统的指标。在CWL框架中,度量是通过单个函数指定的,该函数可用于派生出许多相关度量:每个项目的预期效用、预期总效用、每个项目的预期成本、预期总成本和预期深度。CWL框架汇集了几种独立的方法来衡量排名列表的质量,并提供了一个基于用户模型的一致框架,用于开发基于效用(收益)和成本的度量。在这里,我们概述了CWL的测量框架;描述cwl_eval架构;并提供如何使用它的例子。我们提供了许多最新指标的实现,包括时间偏差增益、u型测量、宝石迷阵测量和基于信息采集的测量,以及以前的指标,如精度、平均精度、折扣累积增益、秩偏差精度和INST。通过在同一框架内提供最先进和传统的指标,我们促进了一种评估搜索有效性的标准化方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信