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.

翻译：自动答案验证可通过为学习者提供适当反馈，以及促进问答系统和在线学习解决方案的广泛普及，从而有助于提升学习效果。已有一些科学问答研究显示，信息检索方法优于神经网络方法，尤其在选择题这类问题中更为显著。我们实现孪生神经网络模型，并针对该问题提出一种通用解决方案。我们将监督式模型与其他基于文本相似度的方案进行了比较。