Abstract: To solve the SVM classification problem of high computational complexity and not suited to large-scale scenes，ACA-SVM with quantum features of Chinese web pages classification is proposed.It improves the algorithm and proposes a strategy for dynamic adjustment of rotation angle.Tests shows that the method improves the accuracy，recall and processing time.

Key words: quantum features, Ant Colony Algorithm-Support Vector Machines（ACA-SVM）, web page classification, dynamic adjustment strategy

摘要： 为了克服SVM网页分类计算复杂度高、不适应大规模场景的问题，提出了将具有量子特性的ACA和SVM进行融合的中文网页分类方法；对算法进行改进，提出了一种动态调整旋转门旋转角的策略。实验表明，该方法在精度、召回率及处理时间上均有明显提高。

关键词: 量子特性, 蚁群算法-支持向量机（ACA-SVM）, 网页分类, 动态调整策略