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人工免疫网络记忆分类器网络文本分类研究 被引量：1

Research of Artificial Immune Network Memory Classifier in Web Text Classification
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摘要 论文在人工免疫记忆分类器用于解决数据分类的基础上,提出将该分类器用于解决文本分类的方法。与两种基于免疫原理的文本分类方法和传统的贝叶斯分类器进行了比较研究。结果表明该分类器在标准文本样本集合上的性能好于其他三种分类器,在小样本分类上具有一定优势。 Based on the application of artificial immune network memory classifier（AINMC） in data classification,it presents a way of using the classifier to solve text classification.It is compared with two kinds of classifier,which is based on the principle of immunity,and traditional Bayesian classification.The results show that it has better performance than the other three classifier on the standard text sample set,and it has some superiority on small set of samples.
作者 莫宏伟 徐立芳
机构地区 哈尔滨工程大学自动化学院
出处 《计算机工程与应用》 CSCD 北大核心 2005年第33期24-27,共4页 Computer Engineering and Applications
基金 国家自然科学基金资助(项目批准号:60305007) 黑龙江省自然科学基金资助(项目批准号:F0210) 哈尔滨工程大学校基础研究基金资助(项目号:HEUF04076)
关键词 人工免疫网络记忆分类器 网络文本分类 小样本 artificial immune network memory classifier,Web text classification,small set of samples
分类号 TP183 [自动化与计算机技术—控制理论与控制工程]
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参考文献14

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二级参考文献15

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计算机工程与应用
2005年 第33期

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