分析了海量数据库产生的原因和特点。
一个屏幕就足以成为记录并且显示各种活动的海量数据库。
A screen both records and displays this database of activities.
知识发现及数据挖掘工具在处理海量数据库时显示了它们的长处。
The knowledge discovery and data mining tool display their strong points in handling the great capacity database.
结果，那些世界领先大学里拥有海量数据库的语源学研究机构也说不出个所以然，真是吾道不孤啊。
It turns out that entire etymology research departments with vast databases at world leading universities don't really have much idea either so I'm in good company.
因此如何针对此类统计分析查询进行优化，缩短查询响应时间就成为了提高海量数据库性能的主要方面。
Thus, how to optimize statistic query and shorten respond time has become an important aspect of excellent performance for the database system.
关系数据库中的索引技术可以快速判断记录重复，但对于频繁更新的海量数据库，维护索引的时间与资源开销较大。
But the cost of time and resource is more for maintaining the index in massive database when its records updates frequently.
深入分析了海量数据库的特点，并在此基础上设计了一个基于中间件的海量数据库异地异构容灾模型FRHDMD。
After study deeply of the characteristics of the Massive Database, we designed a Framework of Remote Heterogeneous Disaster-tolerance for Massive Database (FRHDMD) based on the Middle-ware.
反恐数据挖掘系统会进行跨海量数据库的搜寻，以发现可疑行为的征兆，这些数据库保存有竭力躲避监控的人员信息。
Counterterrorism "data mining" systems hunt for signs of suspicious activity across vast databases of information about people who donot wish to be spied upon.
实验结果表明，PSS算法及其并行化算法是一种高效的数据分类算法，尤其适用于解决海量数据库中的数据分类问题。
The test results show that the PSS algorithm as well as its parallel algorithms are high efficient when they are used in classification of massive database.
流行的观点认为EDM需要海量数据库来存储组织所处理的所有数据，但是事实上并非如此，EDM仅仅是一个公共逻辑数据模型。
Unlike the popular myth that EDM requires a mega-database that stores all the data that an organization deals with, it is only a common logical data model.
大多数搜索引擎的工作方式是：在Web上爬行，索引并过滤在海量数据库中找到的内容，然后搜索这些数据库以找到匹配特定搜索查询的结果。
Most search engines work by crawling the Web, indexing and filtering the content they find into massive databases, and searching these databases to find results matching a particular search query.
基因组数据库保存了海量的原始数据。
Genetics databases hold extremely large amounts of raw data.
它可以在你的iPad屏幕上提供一个海量的在线电影数据库，使得你可以很容易的找到一个人，并且发现你是在哪里看到过的。
It optimises the enormous online movie database for your iPad screen and makes it very easy to look up a person and find out just where you've seen them before.
但是由131家公司所安装的超过三分之二的追踪文件（2224个）都有问题，这些公司中的不少都涉足此类交易：追踪Web用户以建立可供售出的海量用户资料数据库。
But over two-thirds—2, 224—were installed by 131 companies, many of which are in the business of tracking Web users to create rich databases of consumer profiles that can be sold.
在海量图像数据库上的实验结果说明了该算法的有效性。
Experiment results on large image database demonstrate the effectiveness of the proposed algorithm.
但是，对于一个使命为“组织全世界的信息，使人人皆可访问”的公司，Facebook的海量个人数据库足以使其成为一个明确的竞争对手。
But for a company whose stated mission is to "organize the world's information and make it universally accessible," Facebook's massive data trove on personal relationships makes it a clear competitor.
本文提出了一种有效的支持海量图像数据库Q BE查询的聚类索引算法。
This paper proposes an indexing algorithm of clustering which supports QBE image retrieval for large image databases.
这就对数据库管理系统提出了挑战，即如何有效地存储和管理海量数据并高效的支持上层的查询。
This is a great challenge to DBMS, because it has to store and manage the massive data efficiently and support SQL queries more effectively.
数据挖掘就是从海量数据中提取知识，又被称为数据库中的知识发现。
Data Mining, also known as knowledge Discovery in Database, distills knowledge from a mass of data.
使用对象关系型数据库来一体化存储和管理海量的GIS基础图形数据和属性数据是近年来GIS领域研究的一项重点内容。
It is an important research content of GIS fields in the recent years to store and manage mass GIS basic graphics data and attribute data using object-relation database.
多维数据库中的超立方体结构应用于对海量数据的多维分析中。
The cube in multidimensional database is used in the multidimensional analysis of the huge data.
从海量的数据中提取知识和信息是数据挖掘解决的主要问题、对处理数据库的规模不断扩大，而导致信息杂乱的主要方法。
The data extracted from the mass of knowledge and information are the major problems in data mining, processing database of scale unceasingly expands, the main methods to information messy.
这一方法灵活廉价，在海量人脸特征数据库中应用将显著提高系统响应速度。
This method is cheap and scalable, and it will obviously shorten the system response time when applied in huge-amount facial feature databases.
数据挖掘技术，可以帮助我们从海量数据中发现有用的模式，已经成为数据库研究的一个新的热点。
Data mining technology can help us discover useful schema from great capacity of data, and has become a new hotspot in database research field.
用户如何从海量图像数据库中快速而又淮确地检索出需要的图像，是目前研究的一项重要课题。
For users, how to retrieve the image quickly and accurately from the large image database, is an important topic in current research.
建立功能强大的影像数据库是海量遥感影像数据组织与管理的必然趋势。
It is an inevitable trend to organize and manage enormous remote sensing image datum with a powerful Database management system.
最后，提出了一种基于国家海量级的空间地理数据库建设的设计。
Finally, Based on a national Bega bytes database, a prototype idea of construction model is put forward.
数据库中多个实体呈树形关联时，对海量数据作多层实体连接运算时要消耗系统大量的内存资源。
Vast memory resource is consumed when great capacity data is retrieved while many layers of entities in a database are re - lated like a tree and join operation is carried out.
本文针对海量离散数据的特点，借鉴分布式数据库、并行运算、网格计算及多线程的思想，提出了一套海量离散数据快速检索方法。
According to the feature of mass discrete data, an efficient retrieval method is stated by referring to the philosophy of distributive database, parallel computing, grid computing and multi-threading.
本文针对海量离散数据的特点，借鉴分布式数据库、并行运算、网格计算及多线程的思想，提出了一套海量离散数据快速检索方法。
According to the feature of mass discrete data, an efficient retrieval method is stated by referring to the philosophy of distributive database, parallel computing, grid computing and multi-threading.
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