Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{203459,
        author = {Shraddha Bapu Tupe and Shravani Arvind Deokar and Sanika  Sanjay Deore and Vaishnavi Appasaheb Nemane},
        title = {Automatic Subjective Answer Evaluation Using Machine Learning and NLP},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {12400-12400},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203459},
        abstract = {The Automatic Subjective Answer Evaluation (ASAE) system is designed to automate the evaluation of descriptive answers using Machine Learning (ML) and Natural Language Processing (NLP). Traditional manual evaluation methods are time-consuming, inconsistent, and prone to human bias. The proposed system uses semantic similarity techniques, NLP preprocessing, and machine learning algorithms to compare student answers with reference answers and generate scores automatically.},
        keywords = {Machine Learning, NLP, Subjective Answer Evaluation, Django, Python, Semantic Similarity},
        month = {May},
        }