支持向量机算法在MOOC课程答疑系统中的研究

Study on MOOC Intelligent Answering Using Support Vector Machine

随着互联网技术和近期MOOC课程的发展,智能答疑系统也受到了更多的关注,应用它能够及时给学生提供学生疑惑的问题答案.智能答疑系统通常包括问句理解、信息检索、答案抽取和选择三个主要部分,且问句分类是问句理解的关键,因为它的准确性将直接影响到最后答案的准确性.以高校计算机基础课程为实际背景,在已有基于支持向量机算法基础上,对该方法进行了改进,并通过训练集和测试集进行了验证.从实验结果看,该方法在高校计算机基础智能答疑系统中有比较好的应用效果.

With the development of Internet technology and the MOOC Courses, the intelligent answering also has drown more attention, because it can solve user unsure questions timely. Intelligent answering system typically includes comprehension questions, information retrieval and answer extraction and selection. Question classification is a part of comprehension questions, which directly affects the accuracy of the final answers. It is verified by the training and test sets using the improving method which is based on support vector machine. The results show this method get high classification accuracy on intelligent answering.