Automated Answer Validation using Text Similarity
Balaji Ganesan Arjun Ravikumar Lakshay Piplani Rini Bhaumik Dhivya Padmanaban Shwetha Narasimhamurthy Chetan Adhikary Subhash Deshapogu
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.