Expert Finding Systems: A Systematic Review

被引:19
作者
Husain, Omayma [1 ,2 ]
Salim, Naomie [1 ]
Alias, Rose Alinda [3 ]
Abdelsalam, Samah [1 ,2 ]
Hassan, Alzubair [4 ]
机构
[1] Univ Teknol Malaysia, Fac Engn, Sch Comp, Skudai 81310, Malaysia
[2] Univ Khartoum, Dept Comp Sci, Khartoum 11111, Sudan
[3] Univ Teknol Malaysia, Azman Hashim Int Business Sch, Skudai 81310, Malaysia
[4] Guangzhou Univ, Sch Comp Sci & Cyber Engn, Guangzhou 510006, Guangdong, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2019年 / 9卷 / 20期
关键词
expert finding systems; expertise retrieval; expertise seeking; SOCIAL NETWORK; RECOMMENDATION SYSTEM; INFORMATION-SEEKING; ACCESSIBILITY; RETRIEVAL; QUALITY; MODELS; PERSPECTIVE; REPUTATION; KNOWLEDGE;
D O I
10.3390/app9204250
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The data overload problem and the specific nature of the experts' knowledge can hinder many users from finding experts with the expertise they required. There are several expert finding systems, which aim to solve the data overload problem and often recommend experts who can fulfil the users' information needs. This study conducted a Systematic Literature Review on the state-of-the-art expert finding systems and expertise seeking studies published between 2010 and 2019. We used a systematic process to select ninety-six articles, consisting of 57 journals, 34 conference proceedings, three book chapters, and one thesis. This study analyses the domains of expert finding systems, expertise sources, methods, and datasets. It also discusses the differences between expertise retrieval and seeking. Moreover, it identifies the contextual factors that have been combined into expert finding systems. Finally, it identifies five gaps in expert finding systems for future research. This review indicated that approximate to 65% of expert finding systems are used in the academic domain. This review forms a basis for future expert finding systems research.
引用
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页数:32
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