"Automatic descriptive answer evaluator using machine learning."

"Automating the evaluation of descriptive answers would be beneficial for academic institutions to efficiently manage the online exam results of their students. Our project involves designing an algorithm to automatically evaluate descriptive answers consisting of multiple sentences. Our approach involves representing the student's answer and comparing it with pre-defined answers created by the staff. To evaluate the answer, we use a pattern-matching algorithm and various modules to achieve efficient evaluation without manual labor. This pattern can be used by many organizations to reduce manpower and save time. Natural Language Processing (NLP) aims to interpret human language in a meaningful way and typically involves machine learning techniques. Evaluating the objective function involves assessing candidate solutions against a portion of the training dataset, usually measured by an error score or loss. While the objective function is easy to define, evaluating it can be costly."