Literaturnachweis - Detailanzeige
| Autor/inn/en | Daud, Ali; Song, Min; Hayat, Malik Khizar; Amjad, Tehmina; Abbasi, Rabeeh Ayaz; Dawood, Hassan; Ghani, Anwar |
|---|---|
| Titel | Finding rising stars in bibliometric networks. |
| Quelle | In: Scientometrics, (2020) 1, S.633-661
PDF als Volltext |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0138-9130 |
| DOI | 10.1007/s11192-020-03466-w |
| Schlagwörter | Finding rising stars (FRS); Ranking; Prediction; Clustering; Analysis; Bibliometric networks |
| Abstract | Abstract Finding rising stars (FRS) is a hot research topic investigated recently for diverse application domains. These days, people are more interested in finding people who will become experts shortly to fill junior positions than finding existing experts who can immediately fill senior positions. FRS can increase productivity wherever they join due to their vibrant and energetic behavior. In this paper, we assess the methods to find FRS. The existing methods are classified into ranking-, prediction-, clustering-, and analysis-based methods, and the pros and cons of these methods are discussed. Details of standard datasets and performance-evaluation measures are also provided for this growing area of research. We conclude by discussing open challenges and future directions in this prosperous area of research. |
| Erfasst von | OLC |
| Update | 2023/2/05 |
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