Web page classification method based on ACA-SVM with quantum features
Web page classification method based on ACA-SVM with quantum features
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发表时间：
2011
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通讯作者：
Zuo Jinglong;Yu Guilan
中科院分区：
文献类型：
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作者：
Zuo Jinglong;Yu Guilan
为解决支持向量机分类算法计算复杂度高、不适合大规模场景的问题，提出了基于量子特征的ACA-SVM中文网页分类方法。对算法进行了改进，提出了一种动态调整旋转角度的策略。实验表明，该方法提高了准确率、查全率和处理时间。
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.