JAVA实现文本聚类，用到TF/IDF权重，用余弦夹角计算文本相似度，用k-means进行数据聚类等数学和统计 知识。,JAVA realization of text clustering, using TF/IDF weight, calculated using cosine angle between the text of similarity, using k-means clustering for data such as mathematical and statistical

用JAVA语言实现的经典聚类算法k-means，聚类与分类不同，它是无监督的过程，,JAVA language used to achieve a classic clustering algorithm k-means, clustering and classification of different, it is the unsupervised process,

k-means 算法接受输入量 k ；然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。 -k-means algorithm to accept input k then n-k of data objects into a cluster in order to make the cluster available to meet: t