The way to establish a certain data clustering property in DB2 is to reorganize the table according to an index.
在DB 2中建立数据聚集属性的方法是根据一个索引对表进行重组。
A crucial step in the analysis process is to enable users to understand the results of the data clustering step.
在分析过程中，一个关键的步骤就是让用户理解数据集群步骤的结果。
InfoSphere Warehouse USES a particularly powerful method for deviation detection that is based on data clustering.
InfoSphereWarehouse使用一种特别强大的方法来进行偏差检测，这种方法基于数据集群。
In summary, the accuracy of statistics depends on the sampling rate, the data skew, and data clustering for data sampling.
总之，统计信息的准确性取决于抽样率、数据倾斜(data skew)以及用于数据抽样的数据群集。
Meanwhile, the research of the stream data clustering algorithm would be useful references to the similar researches.
同时，本文对流数据聚类算法的研究，对于促进同类问题的研究具有一定的理论价值和借鉴意义。
This paper proposes a solving method of grid granularity in spatial data clustering.
提出一种空间数据聚类中的网格粒度求解方法。
The experiment results demonstrate its validity over directional higher-dimension data clustering.
实验结果表明，该算法能有效地对高维的方向性数据进行聚类。
The universality of these data makes researches on high dimensional data clustering more and more important.
由于高维数据存在的普遍性，高维数据的聚类分析具有非常重要的意义。
The result of the example shows that the new algorithm can efficiently solve data clustering analysis problems.
通过实例验证，表明该新算法能够有效地解决数据聚类分析问题。
Recently, the graph-theoretical approaches are widely used in the fields of data clustering and image segmentation.
近年来，基于图论的聚类算法被广泛地应用在数据聚类和图像分割之中。
Combined with semantic similarity of text data, this paper gives a method of text data clustering based on semantic density.
结合文本数据的语义相似度，给出一种基于语义密度文本数据聚类的方法。
This algorithm can be used in data clustering and face detection. Its effectiveness has been proven by the experiment results.
这个算法可以用于数据聚类和人脸识别方面，实验结果也证明了该算法的效果。
Data mining is the core topic of this paper. Basically, it includes associate rule founding, data clustering and data assorting.
数据挖掘是本课题的研究核心，主要包括关联规则发现、数据聚类和数据分类。
In recent years, with the application of clustering, high dimensional data clustering is becoming more common, and more important.
近年来随着聚类应用领域的扩展和深入，高维数据聚类越来越普遍，也越来越重要。
Self Organizing Map is a method of artificial neural network, which implements pattern recognition and data clustering simultaneously.
自组织特征映射是一种人工神经网络方法，可以同时实现模式识别和数据分类。
Based on the traditional fuzzy C-means clustering algorithm, a new fuzzy C-means clustering algorithm for interval data clustering is proposed.
在传统模糊c -均值聚类算法的基础上，提出了一种新型区间值数据模糊聚类算法。
Seven kinds of spatial data clustering approaches are studied. And the technique to solve the problem of Constraint-based Spatial Cluster Analysis is explored.
系统研究了七种典型的空间数据聚类方法，积极探索基于约束条件的空间聚类问题的解决方案；
In view of the similarities between data clustering analysis and optimization questions, this paper deals with data clustering analysis by using simulation anneal algorithms.
本文针对数据聚类分析和最优化问题的相似点，用模拟退火算法进行聚类分析。
We design and implement the artificial immune network algorithm, and successfully apply this algorithm in solving a pattern recognition problem and a data clustering problem.
在此基础上，设计和实现了人工免疫网络算法，并应用该算法成功解决了一个模式识别和数据聚类问题。
Data clustering offers a solution to this problem.
数据集群为这个问题提供了一个解决方案。
Data clustering is an important problem in data mining.
数据聚类是数据挖掘中的一个重要课题。
Data clustering can have an especially large impact on data warehouse query performance, because rows are often retrieved in large Numbers.
数据聚簇对于数据仓库查询性能的影响尤其显著，因为常常在一个查询中获取许多行。
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.
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.
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。
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