Question identification in Chinese micro-texts

Le Tian, Xipeng Qiu, Xuanjing Huang

Abstract: Micro-blogs have become very convenient places to ask questions and seek information. In this paper, we focus on automatically identifying questions (the micro-texts which are asked to seek information or help) from Chinese micro-texts. Based on the characters of Chinese question, we investigate various rule-based and learning-based methods to recognize questions. In addition to identify the questions, we also distinguish whether a question can be answered with sufficient conditions. The experimental results on Chinese micro-texts show that our proposed dependency tree pattern is effective for question identification.