A Multi-match Approach to the Author Uncertainty
Problem
Stephen F.Carley[1];Alan L.Porter[1,2];Jan L.Youtie[3];;
【期刊名称】《数据与情报科学学报：英文版》 【年(卷),期】2019(000)002
【摘要】Purpose:The ability to identify the scholarship of individual authors is essential for performance evaluation.A number of factors hinder this endeavor.Common and similarly spelled surnames make it difficult to isolate the scholarship of individual authors indexed on large databases.Variations in name spelling of individual scholars further complicates matters.Common family names in scientific powerhouses like China make it problematic to distinguish between authors possessing ubiquitous and/or anglicized surnames(as well as the same or similar first names).The assignment of unique author identifiers provides a major step toward resolving these difficulties.We maintain,however,that in and of themselves,author identifiers are not sufficient to fully address the author uncertainty problem.In this study we build on the author identifier approach by considering commonalities in fielded data between authors containing the same surname and first initial of their first name.We illustrate our approach using three case studies.Design/methodology/approach:The approach we advance in this study is based on commonalities among fielded data
A Multi-match Approach to the Author Uncertainty Problem
