Smirnova, N., Mayr, P. Embedding models for supervised automatic extraction and classification of named entities in scientific acknowledgements. Scientometrics (2023). https://doi.org/10.1007/s11192-023-04806-2
Acknowledgments in scientific papers may give an insight into aspects of the scientific community, such as reward systems, collaboration patterns, and hidden research trends. The aim of the paper is to evaluate the performance of different embedding models for the task of automatic extraction and classification of acknowledged entities from the acknowledgment text in scientific papers.