表2: 基于数据分类的域分析
有时候，急迫的问题是必须处理数据分类。
Sometimes, the pressing issue has to do with data categorization.
随着数据集的不断增加，数据分类也会不断扩充。
The data catalogs will continue to grow as datasets are added.
您可以认为它是一项在模型层完成的任务，因为要给数据分类。
You could argue it's a task to be accomplished in the Model layer, since you're categorizing the data.
表格(Tables)软件还处在测试期，目前添加了更多数据分类和过滤功能。
The Tables app, still in beta, now has the ability to do more data sorting and filtering.
ICMRME提供的服务使应用程序能够理解文本或文本和特定对象之间的关系(例如，个性化或一般数据分类应用程序)。
ICM RME provides services to applications that need to understand text or correlate between text and certain objects (for example, personalization or general data classification applications).
这看上去像是分类树的一大优势—它无需有关数据的大量信息就能创建一个十分准确且信息丰富的树。
That's seemingly the big advantage of a classification tree - it doesn't require a lot of information about the data to create a tree that could be very accurate and very informative.
除用于收集世卫组织分类使用的数据之外，世卫组织不会为其他任何目的使用这些信息，也不会将这些信息传递到世卫组织之外。
This information will not be used by WHO for any purpose other than compiling data on the use of WHO classifications and shall not be transmitted outside of WHO.
这些错误表明在我们的模型中出了问题，我们的模型正在错误地分类某些数据。
These errors indicate we have problems in our model, as the model is incorrectly classifying some of the data.
重复上述步骤几次以分类示例数据的更多短信。
Repeat the previous step several times to classify more short messages from you sample data.
生成的逻辑数据模型保留术语表分类。
Resulting logical data model retains glossary classifications.
我们用于分类示例的数据集所围绕的仍然是我们虚构的BMW经销店。
The data set we'll use for our classification example will focus on our fictional BMW dealership.
我们为何要使用与分类例子中相同的数据集呢？
Why are we using the same data set we used in the classification example?
在本文中，我们将解释一个特殊的辅助工具，它允许用户排列、分类和比较大量数据。
In this article, we'll explain one particular assistant that allows users to arrange, classify, and compare potentially large quantities of data.
本系列后续的文章将会涉及挖掘数据的其他方法，包括群集、最近的邻居以及分类树。
Future articles will touch upon other methods of mining data, including clustering, Nearest Neighbor, and classification trees.
目前，我们使用我们业务系统的一个大型数据存储库来帮助我们对会员进行分层或分类。
We currently use a large repository of data from our operational systems to help us stratify, or classify, members.
MQT可以根据以下用数据填充它们时所使用的机制来分类
MQTs can be classified according to the mechanism that is used to populate them with data as follows
解释GoogleBase如何使用条目类型和属性对数据进行分类？
Explained how Google Base classifies data using item types and attributes.
收集预先分类的数据，它们将构成文集的基础。
Gather pre-categorized data that will form the basis of a corpus.
数据得以正确地分类排列时，分析效果最好。
与非结构化数据不同，可以使用描述性标签对元素进行分类。
Unlike unstructured documents, the individual elements can be classified using descriptive labels.
列可用于分类数据。
RDF数据被SPARQL引擎分类、交叉引用和转换成XML。
The RDF data is sorted, cross-referenced, and converted to XML by a SPARQL engine.
因为大部分类数据存储在ROMClass中，因此可以节省虚拟内存。
Because the majority of class data is stored in the ROMClass, this is where the virtual memory savings are made.
然后可以用额外的元数据(如属性和分类)对文档和逻辑部分进行注释。
The document and the logical parts can then be annotated with additional metadata, such as properties and classification.
这个爬行/索引过程在没有人类干预的情况下执行，既最大化了效率，也避免了数据归集和分类方面的偏差。
This crawling/indexing process is performed without human intervention, both to maximize efficiency and to avoid biases in data collation and categorization.
通常，大多数APM系统将跟踪程序提交的数据组织到某种分类的层次结构中。
Most APM systems typically organize data submitted by tracers into some sort of categorized and hierarchical structure. Figure 2 illustrates the general flow of this data capture.
您可能见到过大整数质因数分解，或是对复杂数据结构的庞大列表进行分类，这些都是长时间运行的操作。
You might see examples of prime factorizations of large integers, or sorting huge lists of complex data structures, and those are certainly long running operations.
您可能见到过大整数质因数分解，或是对复杂数据结构的庞大列表进行分类，这些都是长时间运行的操作。
You might see examples of prime factorizations of large integers, or sorting huge lists of complex data structures, and those are certainly long running operations.
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