{"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.