Learning to Solve Arithmetic Word Problems with Verb Categorization
Learning to Solve Arithmetic Word Problems with Verb Categorization
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DOI：
10.3115/v1/d14-1058
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发表时间：
2014-10
期刊：
影响因子：
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通讯作者：
Mohammad Javad Hosseini;Hannaneh Hajishirzi;Oren Etzioni;Nate Kushman
中科院分区：
文献类型：
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作者：
Mohammad Javad Hosseini;Hannaneh Hajishirzi;Oren Etzioni;Nate Kushman
本文提出了一种学习解决简单算术字题的新方法。我们的系统ARIS分析问题陈述中的每个句子，以识别相关变量及其值。然后，ARIS将这些信息映射到表示问题的方程中，并启用其（简单的）解决方案，如图1所示。本文分析了“体裁”算术词问题，确定了这类问题中使用的7类动词。ARIS学习动词分类的准确率为81.2%，能够解决标准小学考题语料库中77.7%的问题。我们报告了这个任务的第一个学习结果，而不依赖于预定义的模板，并公开了我们的数据。1
This paper presents a novel approach to learning to solve simple arithmetic word problems. Our system, ARIS, analyzes each of the sentences in the problem statement to identify the relevant variables and their values. ARIS then maps this information into an equation that represents the problem, and enables its (trivial) solution as shown in Figure 1. The paper analyzes the arithmetic-word problems “genre”, identifying seven categories of verbs used in such problems. ARIS learns to categorize verbs with 81.2% accuracy, and is able to solve 77.7% of the problems in a corpus of standard primary school test questions. We report the first learning results on this task without reliance on predefined templates and make our data publicly available. 1