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| 用于Web文本分类的快速KNN算法 | |
| 引用本文： | 王煜,白石,王正欧.用于Web文本分类的快速KNN算法[J].情报学报,2007,26(1):60-64. |
| 作者姓名： | 王煜 白石 王正欧 |
| 作者单位： | 1. 河北大学数学与计算机学院,保定,071002;天津大学系统工程研究所,天津,300072 2. 沧州市城建档案馆,沧州,061000 3. 天津大学系统工程研究所,天津,300072 |
| 摘 要： | KNN算法是一种简单、有效、非参数的Web文本分类方法。传统KNN方法的明显缺陷是样本相似度的计算量很大,使其在具有大量高维样本的Web文本分类中缺乏实用性。本文提出一种快速查找精确的k个最近邻的FKNN(Fast-k-Nearest-Neighbor)算法。FKNN算法首先选择一个样本作为基准点,并将所有样本按照距基准样本的距离进行排序并建立索引表,然后根据索引表和有序队列查找k个最近邻,减小了查找范围,极大降低了相似度计算量。 |
| 关 键 词： | 文本分类 相似度 |
| 修稿时间： | 2006年1月18日 |
A Fast KNN Algorithm Applied to Web Text Categorization |
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| Wang Yu,Bai Shi,Wang Zhengou.A Fast KNN Algorithm Applied to Web Text Categorization[J].Journal of the China Society for Scientific andTechnical Information,2007,26(1):60-64. | |
| Authors: | Wang Yu Bai Shi Wang Zhengou |
| Abstract: | The KNN is a simple,valid and non-parameter method applied to WEB text categorization.The traditional KNN has a fatal defect that time of similarity computing is huge.The practicality will be lost when the KNN is applied to WEB text categorization with high dimension and huge samples.In this paper,a method ealled FKNN (Fast-k-Nearest-Neighbor) is presented which can search the k nearest neighbors quickly.In the method,all samples are sorted based on the similarity between itself and the fiducial sample,k nearest neighbors are searched in the sorted queue and the index is created,then the searching scope is reduced.Subsequently the time of similarity computing is decreased largely. |
| Keywords: | KNN |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |