另外，字典可以通过聚类自动生成。
通过聚类分析，发现舌、脉、主症聚类有明显规律。
Obvious disciplinarian was found of tongue, pulse and main symptoms through cluster analysis.
聚类分析是数据挖掘中的一项重要技术，通过聚类可以发现隐藏在海量数据背后的知识。
Clustering analysis is an important research field of data mining, through which we can find hidden knowledge behind mass data.
该算法将ISODATA算法引入图像检索领域，实现了通过聚类算法来优化图像检索的目的。
By introducing ISODATA into the field of image search, this algorithm can realize the purpose of optimizing the image retrieval by the cluster algorithm.
该方法可概括为分割、检索、合成三个步骤首先通过聚类将连续运动捕获数据分割为运动基元；
The innovations of this paper are listed as follows:(1) A new virtual human motion synthesis technology based on motion capture data is proposed.
聚类检索通过聚类产生相似数据的分类，并以此为基础进行数据查询，从而提高数据检索的效率。
Cluster retrieval method can produce classification of similar data through clustering, and data searching is processed based on this. It can effectively enhance the data retrieval efficiency.
通过聚类，人们能够识别密集的和稀疏的区域，因而发现全局的分布模式，以及数据属性之间有趣的相互关系。
By clustering, one can identity dense and sparse regions, therefore, discover overall distribution patterns and interesting correlations among data attributes.
该聚类算法通过曲线拟合技术来实现文本的自动阈值确定和聚类划分，并最终通过聚类间的迭代和结果修正来完成整个聚类过程。
The clustering method USES curve-fitting to implement the text clustering by auto threshold-detection means, and complete the whole clustering process through result revising phase.
分析了目前的入侵检测技术，提出了使用聚类算法进行网络入侵检测的方法，并通过试验说明了该方法的应用效果。
This paper analyses the current intrusion detection techniques, brings forward a technique that applies cluster algorithm to network intrusion detection, and shows the effect through an experiment.
文章依据员工的收入水平，通过分层聚类和对应分析对员工需求层次和需求重点进行了明确的界定，并针对不同的收入水平提出了不同的激励措施。
Through HC and ANACOR, this paper intends to give a clear definition of the employees' demand levels and their key demand, and suggests various incentives based on different income levels.
规则学习模块通过自组织聚类过程自动生成规则。
In the rules learning mode, the rules can be produced automatically through the cluster process.
该文通过对现有群体智能理论和聚类算法的研究，提出了一种基于群体智能理论的聚类模型，并在此基础上给出了一种优化蚁群聚类算法。
This paper provides a model of the clustering and an optimized ant colony-clustering algorithm which is based on the swarm intelligence and that mathematic model is provided at the same time.
该方法以DEA有效为聚类标准，通过逐步寻找DEA有效单元的方法从而达到聚类的目的。
The new method USES DEA efficiency as a clustering standard and looks for DEA effective units step by step so as to cluster.
通过对模糊c均值算法聚类特性的分析，引入了约束函数及模式相似度的概念，提出了改进的FCM算法。
With the clustering feature analyzed, restrained function and pattern similarity are introduced. Then the algorithm of improved FCM is presented.
聚类通过比较数据的相似性和差异性，能发现数据的内在特征及分布规律，从而获得对数据更深刻的理解与认识。
By contrasting the similarity and dissimilarity in data, clustering can find out the data's inner characteristic and distribution rule, so we can obtain the further understanding.
通过评价在两个消歧任务上的聚类结果，你需要探讨不同表示方法的优点并研究学习方法的性质。
By evaluating the resultant clustering on two disambiguation tasks, you will explore the merits of different representations and study the properties of the learning method.
通过三组数据对这个聚类有效性函数的判决功能和鲁棒性进行了对比研究。
Experimental results show the effectiveness and robustness of this cluster validity function by three data sets.
为了构建聚类代表，算法通过构造最佳匹配树，合并树，修剪树三步来实现。
The cluster representative was constructed by three successive steps named Tree matching, Tree merging and Tree pruning.
通过线性变换得出模糊聚类指标及模糊子集。
Index of fuzzy cluster and fuzzy subset can be obtained through linear transform.
通过定量分析传感器节点的通信能量消耗，建立了聚类首领剩余能量与通信流量的关系模型。
Through analyzing communication energy dissipation of wireless sensor nodes quantitatively, the relational model of cluster heads' residual energy and communication traffic was established.
通过概念聚类识别孤立点，运用规划识别技术和贝叶斯因果网络实现目标的预测、识别，最终实现系统自学习。
The system applies conceptual clustering technology to recognize outliers, and uses plan recognition and causal network to predict and recognize the target.
首先，通过减法聚类来确定初始系统，然后再进行学习训练。
First, determining the initial system by the method of subtractive clustering. Second, learning the system.
该算法通过引入聚类有效性函数，实现了最优特征数目的自动确定。
The optimal feature number is decided automatically by the introduced cluster validity function.
提出了一种通过调整减法聚类半径优选模糊规则的软测量建模方法。
A soft sensor modeling method is presented which selects optimal fuzzy rules by tuning the radius of a subtractive cluster center.
通过在类的边界区域进行细化来提高网格划分的质量从而提高聚类的精度。
It improves the quality of grid partition by refining the edge of the class, so improves the quality of the clustering.
通过计算待评价对象与各聚类中心的距离，实现对其分类和方案的评价。
The classification and evaluation are realized by calculating the distance of the object and the cluster center.
通过邻接矩阵，计算网络的聚类系数。聚类系数是复杂网络中一个重要参量。
Through the adjacency matrix, computing networks, clustering coefficient. Clustering coefficient is a complex network, an important parameter.
提出一种新的基于模型的聚类算法，通过优化给定的数据和数学模型之间的适应性发现数据对模型的最好匹配。
In this paper, a new clustering algorithm based on model is proposed, it finds the best fit of the given data to mathematical model by optimizing the fit between the data and model.
提出一种新的基于模型的聚类算法，通过优化给定的数据和数学模型之间的适应性发现数据对模型的最好匹配。
In this paper, a new clustering algorithm based on model is proposed, it finds the best fit of the given data to mathematical model by optimizing the fit between the data and model.
应用推荐