计算机工程与科学2011，Vol.33Issue(12)：94-98,5.DOI:10.3969/j.issn.1007-130X.2011.12.017
基于改进的免疫克隆支持向量机网页分类研究
Research of Web Page Classification Based on Improved Immune Clone-Support Vector Machine
摘要
Abstract
Web page classification is an extended hot field for solving the problem of information o-verload ,with the excellent ability to learn, support vector machine shows a specific advantage in solving high dimensional problems. A new classification algorithm based on the combination of support vector machine and improved immune clone is proposed after the research of support vector machines and standard immune clones. As the standard algorithm achieves antibody variants through inverting randomly some bits in antibody coding, so it is not strong in searching capability, for this deficiency, the paper distinguishes memory units and normal units, defines adaptive probability for the memory units, thereby strengthens search capability in the neighborhood of the current optimal solution, thus accelerates the speed to find the global optimal solution. A lot of experiments have shown that the improved algorithm which has a better parameters selection effect and a higher efficiency is a web page classification method with high accuracy and efficiency.关键词
网页分类/支持向量机/特征提取/参数选择/免疫算法Key words
Web page classification/support vector machine/feature extraction/parameter selection/ immune algorithm分类
信息技术与安全科学引用本文复制引用
张素琪,刘恩海,贺亚,董永峰..基于改进的免疫克隆支持向量机网页分类研究[J].计算机工程与科学,2011,33(12):94-98,5.基金项目
2011年天津市科技计划项目(11JCYBJC00200) （11JCYBJC00200）
