An optimized BERT fine-tuned model using an artificial bee colony algorithm for automatic essay score prediction.

ABSTRACT:

Background

The Automatic Essay Score (AES) prediction system is essential in education applications. The AES system uses various textural and grammatical features to investigate the exact score value for AES. The derived features are processed by various linear regressions and classifiers that require the learning pattern to improve the overall score.

Issues

Moreover, the classifiers face catastrophic forgetting problems, which maximizes computation complexity and reduce prediction accuracy. The forgetting problem can be resolved using the freezing mechanism; however, the mechanism can cause prediction errors.

Method

Therefore, this research proposes an optimized Bi-directional Encoder Representation from Transformation (BERT) by applying the Artificial Bee Colony alg

SUBMITTER: Chassab RH 

PROVIDER: S-EPMC11623024 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature