| Autor: |
Rohith H P, Srinivas D B, Deepika K M, Kavitha Sooda, Karunakara Rai B |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
International Journal on Recent and Innovation Trends in Computing and Communication. 11:20-25 |
| ISSN: |
2321-8169 |
| DOI: |
10.17762/ijritcc.v11i1.5983 |
| Popis: |
The human evaluation of essays has become a very time-consuming process as the number of schools and universities has grown. The available software entities are unable to assess the sentiment associated with essays. Thus, we propose a model using Natural Language Processing to assess the essay based on both grammar and sentiment associated with the essay by using linear regression and ULMFiT (Universal Language Model Fine-tuning for Text Classification) models. Evaluation of essay is done in two parts. Part one is on essay grading with respect to grammar with maximum 12 and minimum 0 grade points and in part two score of 0/1 for sentiment analysis with 0 being negative and 1 being positive. The model can be used to score the essay and discard any essay with a score less than a specified value or specified sentiment score. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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