Editorial: Mining Scientific Papers, Volume II: Knowledge Discovery and Data Exploitation
- PMID: 35782365
- PMCID: PMC9241486
- DOI: 10.3389/frma.2022.911070
Editorial: Mining Scientific Papers, Volume II: Knowledge Discovery and Data Exploitation
Keywords: academic search; citation content analysis; computational linguistics; natural language processing; scientific papers; scientometrics; text mining.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Comment on
- Editorial on the Research Topic Mining Scientific Papers, Volume II: Knowledge Discovery and Data Exploitation
References
-
- Cabanac G., Frommholz I., Mayr P. (2020a). “Bibliometric-enhanced information retrieval 10th anniversary workshop edition,” in Advances in Information Retrieval, Volume 12036, eds J. M. Jose, E. Yilmaz, J. Magalhes, P. Castells, N. Ferro, M. J. Silva, and F. Martins (Cham: Springer International Publishing), 641–647.
-
- Ermakova L., Bordignon F., Turenne N., Noel M. (2018). Is the abstract a mere teaser? Evaluating generosity of article abstracts in the environmental sciences. Front. Res. Metr. Analyt. 3:16. 10.3389/frma.2018.00016 - DOI
-
- He J., Chen C. (2018). Temporal representations of citations for understanding the changing roles of scientific publications. Front. Res. Metr. Analyt. 3:27. 10.3389/frma.2018.00027 - DOI
Publication types
LinkOut - more resources
Full Text Sources
