Features in extractive supervised single-document summarization: case of Persian news (2024)
Journal Article
Rezaei, H., Mirhosseini, S. A. M., Shahgholian, A., & Saraee, M. (in press). Features in extractive supervised single-document summarization: case of Persian news. Language Resources and Evaluation, 1 - 19. https://doi.org/10.1007/s10579-024-09739-7

Text summarization has been one of the most challenging areas of research in NLP. Much effort has been made to overcome this challenge by using either abstractive or extractive methods. Extractive methods are preferable due to their simplicity compar... Read More about Features in extractive supervised single-document summarization: case of Persian news.