Multiple server instances can be scaled using standard WebSphere clustering techniques.
可以使用WebSphere群集技术衡量多个服务器实例。
For larger number of users, load balancing and server clustering techniques are unavoidable.
对于更大数量的用户，负载均衡和服务器集群技术就在所难免了。
This function is enabled by features of the application server to support dynamic clustering techniques.
这个功能是由支持动态集群技术的应用程序服务器的特性实现的。
This paper describes an approach where machine learning clustering techniques are applied to improve the matching process.
文中描述了一个应用机器学习聚类技术改善匹配过程的方法。
IBM WebSphere Process Server provides many different ways to use clustering techniques to address availability and scalability.
IBMWebSphereProcessServer提供了许多使用集群技术解决可用性和可伸缩性的不同方法。
It would normally be better, though, to use MQ clustering techniques to achieve this, giving each application server its own queue manager.
但是在通常情况下，一种更好的解决此问题的方法是使用MQ集群技术，这将为每个应用程序服务器提供自己的队列管理器。
We also discuss the increment clustering techniques which can improve the efficiency of cluster analysis with the prophase results to deal with the increment data.
我们还探讨了增量聚类技术，在数据不断增长的情况下，增量式聚类技术能够利用前期聚类的计算结果，充分提高聚类分析的效率。
This paper aims at outlier mining, and proposes an algorithm of outlier mining called AOMGC based on grid clustering techniques, with the existing algorithm of LOF.
针对离群点的挖掘，在现有的LOF算法的基础上，提出了一种基于网格聚类技术的离群点挖掘算法AOMGC。
Clustering techniques usually have to assign the number of clusters, but whether the result really reflects the classification of users needs verification on the validity of cluster.
聚类技术通常必须指定一个聚类个数，这样给出的聚类结果是否合理，是否真正反映了用户群的分类就需要进行聚类有效性的验证。
Clustering of relational databases for scalability and availability is a well established discipline, and so we will not spend time discussing techniques for clustering relational databases.
集群关系数据库以获得可伸缩性和可用性是一种业已建立的良好规程，因此我们不再花费时间讨论集群关系数据库的技术。
At first, we summarize the key techniques used in the content-based video retrieval, such as shots division, video character analysis, shots clustering, etc.
本文首先分析了基于内容的视频检索的关键技术。总结了镜头分割、视频流特征分析和镜头聚类方面的相关研究和算法。
After discussing the concepts, techniques and algorithms about clustering, a grid and density based cluster algorithm was proposed.
讨论数据挖掘中聚类的相关概念、技术和算法。
The system adopts the techniques of initialization of state mapping plane, calibration of unknown pattern and on-line identification and this makes plant condition clustering efficiently.
该系统采用状态映照平面初始化方法、未知模式标定技术和在线识别技术，并结合知识库和规则推理的运用，有效地实现设备状态的分类。
One for clustering toolbox, with principal component analysis, fuzzy techniques, such as Matlab source code and application procedures for Demo.
一个用于聚类的工具箱，内有主元分析、模糊等技术的Matlab源代码和应用实例程序Demo。
There are various applications of clustering analysis techniques in the field of image retrieval.
在图像检索领域，聚类分析技术有着广泛应用。
Techniques, such as server clustering, support redundant work loads on multiple physical serve.
服务器集群技术，如，支持冗余工作负载在多个物理服务。
Techniques, such as server clustering, support redundant work loads on multiple physical serve.
服务器集群技术，如，支持冗余工作负载在多个物理服务。
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