Research Article
Attention-Based Bidirectional Long Short-Term Memory Neural Network for Short Answer Scoring
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@INPROCEEDINGS{10.1007/978-3-030-66785-6_12, author={Linzhong Xia and Mingxiang Guan and Jun Liu and Xuemei Cao and Dean Luo}, title={Attention-Based Bidirectional Long Short-Term Memory Neural Network for Short Answer Scoring}, proceedings={Machine Learning and Intelligent Communications. 5th International Conference, MLICOM 2020, Shenzhen, China, September 26-27, 2020, Proceedings}, proceedings_a={MLICOM}, year={2021}, month={1}, keywords={Natural language processing Short answer scoring Long Short-Term memory Attention mechanism Quadratic Weighted Kappa}, doi={10.1007/978-3-030-66785-6_12} }- Linzhong Xia
Mingxiang Guan
Jun Liu
Xuemei Cao
Dean Luo
Year: 2021
Attention-Based Bidirectional Long Short-Term Memory Neural Network for Short Answer Scoring
MLICOM
Springer
DOI: 10.1007/978-3-030-66785-6_12
Abstract
The automatic short answer scoring by using computational approaches has been considered the best way to release the workload of human answer raters. In this paper, we designed a novel neural network architecture which is attention-based bidirectional long short-term memory to implement the task of automatic short answer scoring. We evaluate our approach on the Kaggle Short Answer dataset (ASAP-SAS). Our experiment results indicate that our model can scoring short answers more accurately in terms of the quality of the results. Meanwhile, our experiment results demonstrate that our model is more effective and efficient than other baseline methods in most cases.
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