A K-Nearest Neighbor Algorithm Based on Cluster in Text Classification
The K-Nearest Neighbor Algorithm (K-NN) is an important approach for automatic text classification. In this paper, cluster was applied In order to overcome the disadvantages of the traditional K-NN algorithm. First Clustering was utilized in training set through an improved K-mean approach to select the most representative samples as cluster center.Then we compute the comparability between the testing samples and the central vector of each cluster. A K-NN algorithm based on cluster was presented ,The experiment results verify that this classification algorithm is much faster than the traditional K-NN algorithm, and it can raise the accuracy.
text classification k-Nearest Neighbor cluster
Chun-Yan WANG Kuo Zhang Yu-Guang YAN Jian-Gang Li
Department of computer science and technology, Changchun Normal College Changchun, China Institute of mechanical science and engineering Jilin University Changchun China Department of computer science and technology, Changchun Normal College Changchun, China
国际会议
长春
英文
225-228
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）