This paper presents an integrated method on question classification for Chinese cuisine question answering (QA) system. First, we exploit the domain knowledge to enrich question preprocessing, then classification features are extracted by means of domain attributes and the rule-based classifier is constructed. Support vector machine (SVM) classifier is used for secondary classification to the questions which cannot be matched with rules. A prototype system based on the proposed method has been constructed and an experiment on 453 natural language questions collected from Internet has been carried out. It achieved an accuracy of 96.22%. Result shows that a small number of linguistically motivated domain features can efficiently classify questions of Chinese cuisine QA system. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.