请在下个月继续关注本系列以了解分布式数据挖掘。
Tune in to this series to learn about distributed data mining next month.
最后，实现了分布式数据挖掘平台原型。
因此本文采用了RMI技术来实现分布式数据挖掘。
So we choose RMI to realize distributed data mining algorithm.
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 grid plays an important role in providing a computational support for distributed data mining and knowledge discovery.
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。
The article discussed in the knowledge grid architecture based on a grid-based distributed data mining process.
基于分布式数据挖掘技术，提出了一种基于自适应蚁群算法的分布式分类规则算法。
A distributed classification rule mining based on ant colony algorithm is proposed, which is based on distributed database structure.
对于这两个问题，传统的数据挖掘技术根本无法解决，因此分布式数据挖掘技术随之而出。
For these two problems can't be solved by traditional data mining, distributed data mining techniques come into being.
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 grid technologies provide effective computational support for the applications. This paper introduces infrastructure of the grid and distributed data mining.
论文把分布式数据挖掘算法运用于入侵检测系统，研究了基于分布式关联规则算法的分布式模式提取。
This paper applies distributed data mining algorithm to IDS, takes some research on distributed pattern extraction which is based on distributed association rules algorithm.
目前，该研究领域的两个重要问题式设计合适的分布式数据挖掘系统的体系结构和相应的分布式挖掘算法。
Presently, the two important matters in this field are that, design for suitable architecture of distributed data mining systems and corresponding distributed mining algorithms.
同时，为了从丰富的数据资源中找到自己需要的有益信息，人们又提出了数据挖掘和分布式数据挖掘的方法。
Moreover, for the sake of picking out useful information from these data resource, the researchers raise data-mining technology and distributed data-mining technology.
在本系列中，您将了解如何管理和组织数据与内容，了解分布式数据挖掘并学习分析信息并向用户呈现的一些技巧。
Throughout the series, you discover how to manage and organize data and content, learn about distributed data mining, and find tips for analyzing and presenting information to users.
有了Hadoop，分布式数据挖掘和分析对所有软件创新者和企业家都是可用的，包括但不限于Google和Yahoo ！这类大企业。
With Hadoop, distributed data mining and analysis is available to all kinds of software innovators and entrepreneurs, including but not limited to big guns like Google and Yahoo!.
分布式数据源数据挖掘的第一个问题是发现。
The first issue with data mining of distributed data sources is discovery.
利用数据挖掘技术提取关键信息，判断是否存在分布式扫描、慢速扫描等行为，并及时报警。
The information can be used to judge whether there is distributed scanning, slowly scanning etc, and alert if so.
讨论了松散耦合的分布式信息系统中的数据挖掘问题。
This paper discusses the problem of data mining in loosely coupled distributed information systems.
为了提高对隐私数据的保护程度和挖掘结果的准确性，提出一种有效的隐私保护分布式关联规则挖掘算法。
In order to raise the level of protection of data privacy and accuracy of the outcome of the excavation, an effective protection of the privacy of distributed algorithms Mining Association Rules Act.
针对分布式系统中的数据挖掘问题，提出了一种新颖高效的分布式元挖掘方法。
Aiming at the problem of data mining in distributed system, a novel and effective meta-mining method is presented.
探讨了利用分布式对象技术和数据挖掘技术来解决网络安全系统自适应性的研究思路。
Discussing the research method that resolve the adaptation of security system using distributed object technique and data mining.
为有效解决分布式攻击，提出了基于多传感器数据融合与挖掘的分布式入侵检测模型。
To solve the distributed attacks efficiently, this paper presents the Distributed Intrusion Detection Model Based on Multisensor Data Fusion and Mining (DIDM).
数据隐私问题引起人们的广泛关注，如何在分布式数据库的环境下挖掘关联规则成为研究的热点。
With the growing concern over data privacy-preserving problem, how to discover association rules from distributed databases becomes one of the hot topics of this field.
随着计算机技术的飞速发展和信息时代的到来，在网络分布式环境下，如何进行有效的数据挖掘已成为数据库研究领域一个新的课题。
With the coming of rapid development of computer technology and information era, how to mine efficient knowledge from under distributed environment becomes a new topic in database research areas.
因此，分布式并行数据挖掘处理模式是目前研究的热点问题之一。
So, distributed and parallel data mining pattern is one of hot problems of research currently.
面对数据的海洋，传统的单机串行算法己经不能适应快速、实时的知识需求，研究面向多机、并行、分布式的数据挖掘模型越来越重要。
The traditional serial algorithm can't do work well for the data ocean quickly and correctly, it also important to research the parallel algorithm.
将多传感器数据融合与数据挖掘技术应用到分布式入侵检测中，可连续和全面地提供网络攻防战场环境态势的综合评估。
By applying Multisensor Data Fusion and Data Mining to intrusion detection, DIDM provides the comprehensive assessment of network attack and defense situations continuously and globally.
通过算法实例验证了算法的正确性和可行性，可以在分布式或者并行环境里实现高效的数据挖掘。
The algorithm is used for the example and shows the correctness and feasibility. It can be used for distribute database and most applicable for distribute calculation.
本文对分布式入侵检测系统进行了介绍，提出了一种基于数据挖掘以及分布式系统架构的入侵检测系统。
This paper introduces a method, data fusion, to intrusion detection system (IDS), and presents a new design of DIDS based on data fusion.
本文对分布式入侵检测系统进行了介绍，提出了一种基于数据挖掘以及分布式系统架构的入侵检测系统。
This paper introduces a method, data fusion, to intrusion detection system (IDS), and presents a new design of DIDS based on data fusion.
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