Mining association rules in grid data mining is discussed and two solutions are presented. One uses the communication mode of local-local to balance the burden of communication among local Web sites.
文章对网格数据挖掘中的关联规则挖掘问题进行了探讨，给出了两种实现方案，一是采用局部-局部的通信模式，各个站点的通信负载比较均衡；
Design mode includes a graphical design surface used for selecting a single data mining model and input table, and a grid used for specifying the prediction query.
设计模式包含用于选择单个数据挖掘模型和输入表的图形设计图面，同时还包含用于指定预测查询的网格。
This paper mainly introduces the development and owl implementation of the user-centered data mining service ontology on Universal Knowledge Grid.
本文主要介绍通用知识网格下以用户为中心的数据挖掘本体的设计和OWL实现。
Taking advantages of grid computing, the new model enhances the power of the traditional complex data mining techniques and improves their performance.
它利用网格计算技术的优势，提高了以往复杂的数据挖掘技术的能力和效率。
The algorithm can be directly applied to data mining, digital grid partitioning and estimation, data partitioning, digital terrain surface simplification, etc.
实现的算法可以直接应用于数据挖掘、数字网格划分与评估、数据分割、数值地形曲面的简化等问题。
In this thesis, the author presents the theory of data mining, and deeply analyzes the algorithms of grid clustering.
本文介绍了数据挖掘理论，对网格聚类算法进行了深入地分析研究。
Research on grid clustering algorithms has become a highly active topic in the data mining research.
网格聚类算法研究已经成为数据挖掘研究领域中非常活跃的一个研究课题。
The grid technologies provide effective computational support for the applications. This paper introduces infrastructure of the grid and distributed data mining.
对于以上的这些应用，网格技术提供了有效的支持，介绍了网格的基础设施以及分布式数据挖掘。
The paper mainly discusses a clustering algorithm based on density and grid in data mining, which has high clustering efficiency and low time complexity.
该文主要讨论数据挖掘中一种基于密度和网格的聚类分析算法及其在客户关系管理中的应用。
The speed of mining outliers from dataset is slow. According to the characteristic of grid, fast outliers mining algorithm was proposed by partitioning the data into a set of units cell firstly.
针对数据集中离群数据的挖掘速度的问题，提出了快速的基于单元格的离群数据挖掘算法。
With the grid and data mining technology and continuous improvement, knowledge-based grid of data mining technology will be widely used.
伴随着网格和数据挖掘技术的不断提高，基于知识网格的数据挖掘技术将得到广泛的应用。
The data mining method based on the Concept Lattice is constituted by the two key steps: construction of concept lattices and extraction of designed grid knowledge.
基于概念格的数据挖掘方法由两个关键步骤构成：概念格的构建和基于构建好的概念格的知识提取。
The method can control and manage the dynamic data grid overall situation ground, can trigger the data mining by order, can scoop out data using association rules by prime number saving.
该方法采用数据网格树对动态数据网格进行全局控制和管理，采用挖掘作业命令的形式触发域挖掘作业，采用素数存储的方法进行了关联规则挖掘。
The grid plays an important role in providing a computational support for distributed data mining and knowledge discovery.
网格为分布式数据挖掘和知识发现提供了有效的计算支持。
The article discussed in the knowledge grid architecture based on a grid-based distributed data mining process.
文中在讨论知识网格体系结构的基础上实现了基于网格的分布式数据挖掘过程。
To overcome the shortcomings of the GCOD, a high-dimensional clustering algorithm for data mining, the paper proposes an intersected grid clustering algorithm based on density estimation (IGCOD).
针对高维聚类算法——相交网格划分算法GCOD存在的缺陷，提出了基于密度度量的相交网格划分聚类算法IGCOD。
To overcome the shortcomings of the GCOD, a high-dimensional clustering algorithm for data mining, the paper proposes an intersected grid clustering algorithm based on density estimation (IGCOD).
针对高维聚类算法——相交网格划分算法GCOD存在的缺陷，提出了基于密度度量的相交网格划分聚类算法IGCOD。
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