Many stream data mining algorithms have been proposed.
学者们已提出大量处理流数据的挖掘算法。
Ih the data mining. Data mining algorithms are introduced and compared.
在数据挖掘中，对数据挖掘的算法进行了介绍和比较。
This article discussed two data mining algorithms: the classification tree and clustering.
本文讨论了两种数据挖掘算法：分类树和群集。
InfoSphere Warehouse contains highly efficient implementations of almost all current data mining algorithms.
InfoSpherewarehouse几乎包含目前所有数据挖掘算法的极为高效的实现。
The ability of data mining algorithms to deal with mass-data becomes more important with the increase in data.
随着数据量的增加，挖掘算法处理海量数据的能力问题日益突出。
Methods Utilization data mining algorithms such as the rough set method to find unknown and potential information.
方法利用粗糙集等数据挖掘的算法，从中发现事先未知、但又是潜在有用的信息。
The book is the first of the technical basis for data mining algorithms described in detail the practical teaching.
本书是国内第一本对数据挖掘技术基础算法进行详细描述的实用性教材。
This article promoted outlier data mining algorithms based on weighted fast clustering to inspect and deal with outlier data effectively.
设计了基于加权快速聚类的异常数据挖掘算法，以便能快速发现异常数据。
Then the characters of stream data mining algorithms are summarized and several techniques that are used in these algorithms are introduced.
然后，总结了流数据挖掘算法的特点，并给出了算法中常用的技术。
However, there are several preprocessing tasks that must be performed prior to applying data mining algorithms to the data collected from server logs.
然而，在将数据挖掘的算法运用到服务器日志上之前，必须对日志数据进行一些预处理。
The models constructed by applying data mining algorithms improve a lot in some aspects, such as efficiency, accuracy, extensibility and adaptability.
应用数据挖掘算法得出的检测模型在检测效率、准确性、可扩展性和自适应性等方面都得到了很大的改进。
The content of this paper includes two respects: research of data mining algorithms and the system structure of the application platform of data mining.
本文的内容包括两个方面：关联规则挖掘算法研究和数据挖掘应用系统体系结构的研究。
Traditional data mining algorithms aiming at static datasets can't be used to mine data streams directly, neither do they have the time and space efficiency.
传统面向静态数据集的算法无法直接用于挖掘数据流，而现有数据流挖掘算法存在时空效率不高的缺陷。
Also, some of data mining algorithms that are commonly used in Web Usage mining are clustering, association rule generation, sequential pattern generation etc.
同时本篇论文也主要提出了一些经常被使用的数据挖掘的算法像聚类挖掘、关联规则挖掘、序列模式挖掘等。
New data mining algorithms can easily be integrated into this platform if they comply with the data model interface and mining model interface of this platform.
只要遵循该平台的数据模型接口和挖掘模型接口，新的数据挖掘算法可以很容易地集成到该平台中去。
The related research aspect includes data warehouse and data mining technologies, construction of CRM systems and design of more effective data mining algorithms.
该领域包括对于数据仓库和数据挖掘技术的研究，CRM系统的构建，以及更加有效挖掘算法的设计等方面。
Compared to the traditional data mining algorithms, the complexity of specific performance of the algorithm in the multi-relational data mining put forward higher requirements.
与传统的数据挖掘算法相比，多关系数据挖掘特有的复杂性对算法的性能提出了更高的要求。
This paper introduces the background, concept and process of data mining technology and data mining algorithms, and elaborates the application actuality of data mining technology.
介绍了数据挖掘技术的背景、概念、流程、数据挖掘算法，并阐述了数据挖掘技术的应用现状。
In the research of data mining-based intrusion detection, data mining algorithms close rely on high standard training datasets, and this limits the validity and generality of results in this field.
在基于数据挖掘的入侵检测研究中往往紧密地依赖于高标准的训练数据集，这严重制约了这一领域研究成果的有效性和通用性。
Data mining is the process of applying algorithms to data to uncover patterns that match a given context or query.
数据挖掘是一个这样的过程，即向数据应用算法以揭露匹配给定上下文或查询的模式。
Data mining revolves around the data and, of course, all the algorithms that we've learned about have revolved around the data.
数据挖掘围绕此数据进行，当然所有我们已经学习过的这些算法也都是围绕此数据的。
Data mining processes apply algorithms to data to uncover patterns matching a given context or query.
数据挖掘过程向数据应用算法，以揭露匹配某个给定上下文或查询的模式。
Secondly, it analyzed association rule and sequence mode used in the process of data mining and compared the main algorithms of association rule and sequence mode.
其次，分析了数据挖掘中所使用的关联规则和序列模式，对关联规则和序列模式的各种挖掘算法进行了比较。
Complying with our data object interface and mining model interface, new mining algorithms can be easily integrated to our system.
只要遵循我们的数据模型接口和挖掘模型接口，新的功能、算法可以很容易地集成到系统中来。
A rough set based data mining system named RSDMS is put forward and realized after the analysis of algorithms in rough set.
在分析了粗集的各种算法之后提出并实现了一个基于粗集的数据挖掘系统RSDMS。
Decision tree algorithms are applied to the data mining of the mammography classification, proposes a medical images classifier based on decision tree algorithm, the experiment results are given.
利用决策树算法对乳腺癌图像数据进行分类，实现了一个基于决策树算法的医学图像分类器，获得了分类的实验结果。
A model of data mining is set up after preparation of data by means of attribute structure, and association rule algorithms are carried out. the data mining result is explained and analysed.
采用了属性构造法进行数据预处理，建立了数据挖掘模型，实现了关联规则算法，并对挖掘结果进行解释与分析。
Clustering is an active study subject in Data Mining. There are many algorithms of clustering that were applied in every field.
聚类分析是数据挖掘领域中一个非常活跃的研究课题，应用于各个领域的聚类算法非常多。
Clustering is an active study subject in Data Mining. There are many algorithms of clustering that were applied in every field.
聚类分析是数据挖掘领域中一个非常活跃的研究课题，应用于各个领域的聚类算法非常多。
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