计算机技术与发展Issue(6)：107-109,113,4.DOI:10.3969/j.issn.1673-629X.2014.06.027
一种改进的K-means数字资源聚类算法
An Improved K-means Clustering Algorithm for Digital Resources
摘要
Abstract
K-means clustering algorithm is a basic analysis method in data mining closeting analysis,which is also the most widely used partitioning algorithm. In this paper,in order to get more fast and effective clustering result from large number of digital resources in digit-al library,aiming at the problems of the traditional K-means algorithm,combining with the features of the digital resources,an improved selection algorithm based on the keyword feature vector for initial clustering center is proposed. On this basis,the traditional K-means clustering algorithm is improved for digital resources clustering and experiment verification. The analysis results show that the algorithm proposed reduces the digital resources clustering cost,improves the clustering efficiency,verifying the feasibility of the algorithm.关键词
K-means算法/数字资源/相似度/初始聚类中心Key words
K-means clustering algorithm/digital resource/similarity/initial clustering center分类
信息技术与安全科学引用本文复制引用
杨永涛,李静..一种改进的K-means数字资源聚类算法[J].计算机技术与发展,2014,(6):107-109,113,4.基金项目
河北省自然科学基金面上项目(F2013203324) （F2013203324）
