A Dataset of Systematic Review Updates

被引:9
作者
Alharbi, Amal [1 ,2 ]
Stevenson, Mark [2 ]
机构
[1] King Abdulaziz Univ, Jeddah, Saudi Arabia
[2] Univ Sheffield, Sheffield, S Yorkshire, England
来源
PROCEEDINGS OF THE 42ND INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR '19) | 2019年
关键词
Systematic review; systematic review update; test collection; evaluation; WORKLOAD;
D O I
10.1145/3331184.3331358
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Systematic reviews identify, summarise and synthesise evidence relevant to specific research questions. They are widely used in the field of medicine where they inform health care choices of both professionals and patients. It is important for systematic reviews to stay up to date as evidence changes but this is challenging in a field such as medicine where a large number of publications appear on a daily basis. Developing methods to support the updating of reviews is important to reduce the workload required and thereby ensure that reviews remain up to date. This paper describes a dataset of systematic review updates in the field of medicine created using 25 Cochrane reviews. Each review includes the Boolean query and relevance judgements for both the original and updated versions. The dataset can be used to evaluate approaches to study identification for review updates.
引用
收藏
页码:1257 / 1260
页数:4
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