【摘要】 对基于混合相似度的HTFC算法进行改进,要做的预处理是:建立向量空间模型,计算文档和链接的混合相似度。算法过程是:首先随机选取√kn个文档进行层次聚类,直到剩k个聚簇为止;对这k个聚簇不断迭代直到集合元素不再变化为止;然后表示出每类;最后通过用户对结果的反馈使得新生成的簇继续迭代,最终满足用户需求。算法第1步采用的是改进的k-means算法,可提高运行效率。反馈机制对原有模型进一步修正,从而提高精度。更多还原

【Abstract】 Improvement of HTFC algorithm based on mixed similarity is engaged.Pre-processes to be done are: buildingup vector space model,computing mixed similarity according to text and hyperlink.Procedure of algorithm is: firstly choose√kn texts at random,ag-glomerative clustering is executed until the number of clusters is leftk,secondly iteration is repeated until elements inthe setkeep stability;then show each class;lastly thefeedback to result can iterate again to stabilize newly cluster.By adoption of improved k-means algorithm,performance can be enhanced.The improvement of feedback to prototype can also upgrade precision.更多还原