VeTo+: improved expert set expansion in academia

Expanding a set of known domain experts with new individuals, sharing similar expertise, is a problem that has various applications, such as adding new members to a conference program committee or finding new referees to review funding proposals. In this work, we focus on applications of the problem...

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Bibliographic Details
Published inInternational journal on digital libraries Vol. 23; no. 1; pp. 57 - 75
Main Authors Chatzopoulos, Serafeim, Vergoulis, Thanasis, Dalamagas, Theodore, Tryfonopoulos, Christos
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2022
Springer Nature B.V
Subjects
Computer Science
Database Management
Digital libraries
Funding
Information Systems and Communication Service
Keywords
Knowledge representation
Semantics
Subject specialists
Scholarly knowledge graphs
Expertise retrieval
Expert finding
Data mining
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Summary:Expanding a set of known domain experts with new individuals, sharing similar expertise, is a problem that has various applications, such as adding new members to a conference program committee or finding new referees to review funding proposals. In this work, we focus on applications of the problem in the academic world and we introduce VeTo+, a novel approach to effectively deal with it by exploiting scholarly knowledge graphs. VeTo+ expands a given set of experts by identifying scholars having similar publishing habits with them. Our experiments show that VeTo+ outperforms, in terms of accuracy, previous approaches to recommend expansions to a set of given academic experts.
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ISSN:1432-5012
1432-1300
DOI:10.1007/s00799-021-00318-7