基于加权矩阵聚类的Web日志挖掘算法 因此，对用户(页面)聚类的过程，也转化为从稀疏矩阵中抽取稠密子矩阵的过程。 2 加权矩阵聚类 矩阵聚类(Matrix Cluster，MC)最初是为客户关系管理(Customer Relationship Management，CRM)提出
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Compared with common matrix clustering algorithms, MPCA overcomes the disadvantages of the distance-based algorithm, such as high complexity of space and time. And it also has great advantages in processsing real-time mining of a large sparse matrix.
与普通的矩阵聚类算法相比,多标记传播聚类算法克服了基于距离的算法在空间复杂性和时间复杂性方面的局限性,在处理Web日志构成的大稀疏矩阵方面具有一定的优势。
参考来源 - 多标记传播聚类算法及其在Web日志挖掘中的应用·2,447,543篇论文数据，部分数据来源于NoteExpress
然后，对传统的矩阵聚类算法进行优化，改进为权值矩阵聚类算法。
Then, for tradition matrix clustering algorithm carries on the optimization, improved as weight matrix cluster algorithm.
实时估计出系统噪声方差矩阵和量测噪声方差矩阵，对状态变量进行灰色聚类，并对滤波矩阵和增益矩阵进行实时自适应调整，计算出状态向量的递推估计值。
Based on real-time estimation of noise matrix and grey clustering of state variable, filter or gain matrix is modulated so as to get an estimation of the state vector.
最后，分析了社会化标注中个性化信息推荐的研究，发现借助矩阵、聚类和网络的分析是三种主要思路。
Finally, studies on personalized information recommendation based on social tagging are analyzed, and find matrix, clustering and network analysis are three primarily methods.
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