中文摘要：

该文针对中文阅读理解问答中的时间、人物、地点、数值、实体、描述六类问题，制定了各类问题回答的启发式规则集。对规则集中每条规则赋予一个相应权值，利用正交表对各规则所对应的权值进行了调优选取，给出了各候选答案句基于相应规则的得分计算方法。该文方法在山西大学自主开发的中文阅读理解语料库CRCC v1．1上进行了实验，在整个语料库上得到了83．09％的HumSent准确率。为了与文献[10]中的最大熵方法比较，该文在与文[10]中完全相同的训练集上调优规则的权值，在相同的测试集上测试，最终得到HumSent准确率81．13％，比最大熵的方法高大约1％，且在全部的六类问题上，该文方法的HumSent准确率都不低于最大熵方法。

英文摘要：

This paper constructs a set of heuristic rules for six types of question regarding to time, human, location, number, entity and description in Chinese QARC system. Each rule is further assigned with a weight optimized by the orthogonal array. Then the calculation of each candidate answer sentence is described over corresponding rules. The experiment on the CRCC v1. 1 （Chinese reading comprehension corpus） built by Shanxi University produces 83.09% HumSent accuracy. Compare with the results of ME-based method, the proposed approach achieves 81.13% HumSent accuracy, which is about 1% higher than the ME-based results on the same training and testing environment.