A Study of automatic tallying-up method for open-ended questions in the questionnaire survey and automatic generation for select appropriate questions

在第一年的研究中，我们开发了句子聚类系统，对问卷调查中的句子进行分类。我们的句子聚类系统根据词素的类型和构成句子的词性对句子进行分类。为了收集系统测试所需的数据，我们进行了问卷调查。我们研究了3种方法，从OCR，语音识别和打字中选择合适的数据输入方法。实验的结果，我们发现最适合的数据输入方法为语音识别。第二年的研究，我们使用一些问卷调查来检验我们的系统。最后一年的研究，主要是将本系统与其他系统进行比较，并对本系统进行了评价。我们研究了基于商业的文本挖掘系统，并将我们的系统与另一个文本挖掘系统进行了比较。实验结果表明，该系统与其他商业文本挖掘系统具有相同的性能。找到了系统的薄弱环节。在未来，我们将继续开发我们的系统。

The First year of our research, we developed the sentence clustering systems which classify the sentences in questionnaire survey. Our sentence clustering system classifies sentences based on the type of morpheme and it's kind of the parts of speech which form the sentences. We questionnaire survey did in order to gather the data which is necessary for the test of our system. We examined 3 methods for suitable data entry method from OCR, speech recognition and typing. The result of experiment, we find the most suited data entry method as speech recognition.2nd year of our research, we examine our system in use some Questionnaire surveys. The result of experiment, we confirm our developed system is effective.The last year of our research, mainly we appraised our system between our system and other system. We research commercial based text mining systems, and we compeer with our system with another text mining system. At the results, we find our system have same performance with another commercial base text mining system. And we find week point of our system. In the future, we continue development of our system.