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Scholarly Recommendation Systems: a Literature Survey by Zitong Zhang; Braja Gopal Patra; Ashraf Yaseen; Jie Zhu; Rachit Sabharwal; Kirk Roberts; Tru Cao; Hulin Wu is a Computer Science article available to read on EtoBox.

What is Scholarly Recommendation Systems: a Literature Survey about?

## Abstract A scholarly recommendation system is an important tool for identifying prior and related resources such as literature, datasets, grants, and collaborators. A well-designed scholarly recommender significantly saves the time of researchers and can provide information that would not otherwise be considered. The usefulness of scholarly recommendations, especially literature recommendations, has been established by the widespread acceptance of web search engines such as CiteSeerX, Google Scholar, and Semantic Scholar. This article discusses different aspects and developments of scholarly recommendation systems. We searched the ACM Digital Library, DBLP, IEEE Explorer, and Scopus for publications in the domain of scholarly recommendations for literature, collaborators, reviewers, conferences and journals, datasets, and grant funding. In total, 225 publications were identified in these areas. We discuss methodologies used to develop scholarly recommender systems. Content-based filtering is the most commonly applied technique, whereas collaborative filtering is more popular among conference recommenders. The implementation of deep learning algorithms in scholarly recommendation

Who reads Scholarly Recommendation Systems: a Literature Survey?

Author

Zitong Zhang; Braja Gopal Patra; Ashraf Yaseen; Jie Zhu; Rachit Sabharwal; Kirk Roberts; Tru Cao; Hulin Wu

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)