Subjective Answer Evaluation Using NLP
Author:
Maharajpet Sheela SORCID, D NavyaORCID, Bhandurge SonamORCID
Publisher
QTanalytics India
Reference13 articles.
1. Annamoradnejad, I., Fazli, M., & Habibi, J. (2020). Predicting Subjective Features from Questions on QA Websites using BERT. 2020 6th International Conference on Web Research, ICWR 2020, 240-244. https://doi.org/10.1109/ICWR49608.2020.9122318 2. Anusha, K., Vasumathi, D., & Mittal, P. (2023). A Framework to Build and Clean Multilanguage Text Corpus for Emotion Detection using Machine Learning. Journal of Theoretical and Applied Information Technology, 101(3), 1344-1350. 3. Bashir, M. F., Arshad, H., Javed, A. R., Kryvinska, N., & Band, S. S. (2021). Subjective Answers Evaluation Using Machine Learning and Natural Language Processing. IEEE Access, 9, 158972-158983. https://doi.org/10.1109/ACCESS.2021.3130902 4. Han, M., Zhang, X., Yuan, X., Jiang, J., Yun, W., & Gao, C. (2021). A survey on the techniques, applications, and performance of short text semantic similarity. Concurrency and Computation: Practice and Experience, 33(5). https://doi.org/10.1002/cpe.5971 5. Jafar, A., Dollah, R., Dambul, R., Mittal, P., Ahmad, S. A., Sakke, N., Mapa, M. T., Joko, E. P., Eboy, O. V., Jamru, L. R., & Wahab, A. A. (2022). Virtual Learning during COVID-19: Exploring Challenges and Identifying Highly Vulnerable Groups Based on Location. International Journal of Environmental Research and Public Health, 19(17). https://doi.org/10.3390/ijerph191711108
|
|