Automated Answer Validation using Text Similarity

• URL: http://arxiv.org/abs/2401.08688v1
• Date: Sat, 13 Jan 2024 07:13:08 GMT
• Title: Automated Answer Validation using Text Similarity
• Authors: Balaji Ganesan, Arjun Ravikumar, Lakshay Piplani, Rini Bhaumik, Dhivya Padmanaban, Shwetha Narasimhamurthy, Chetan Adhikary, Subhash Deshapogu
• Abstract summary: Information retrieval methods outperform neural methods, especially in the multiple choice version of this problem. We implement Siamese neural network models and produce a generalised solution to this problem.
• Score: 0.5025737475817937
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Automated answer validation can help improve learning outcomes by providing appropriate feedback to learners, and by making question answering systems and online learning solutions more widely available. There have been some works in science question answering which show that information retrieval methods outperform neural methods, especially in the multiple choice version of this problem. We implement Siamese neural network models and produce a generalised solution to this problem. We compare our supervised model with other text similarity based solutions.

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