Scholarly recommendation systems: a literature survey

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