对于MIML数据也是如此。
The output of that analysis is a MIML file.
这种分析的输出是一个MIML文件。
Figure 7 shows another possible schema for MIML data.
图7显示了另一种可用于MIML数据的模式。
Listing 7 shows how to index all the keyword values in the MIML XML format.
清单7展示了如何为MIMLxml格式中的所有关键词值建立索引。
The optional dimensions stem from the standard keyword categories in the MIML data.
可选的维表源于MIML数据中的标准关键词类别。
A MIML file is a well-formed XML document whose root element is, as shown in Figure 4.
MIML文件是一种格式良好的XML文档，其根元素是，如图4所示。
Since you often analyze many such documents, the MIML file typically has many elements.
由于您经常要分析很多这样的文档，所以MIML文件通常有很多个元素。
Also, MIML data shredded into a relational is more easily accessible for most BI tools.
而且，对于大多数BI工具而言，被分解到关系表中的MIML数据更易于访问。
In the normal flow, the MIML is input into the indexing step and a text index is created.
按照通常的流程，首先将MIML作为输入提供给索引构建步骤，创建一个文本索引。
This has a significant impact on the time it takes to ingest a large amount of MIML data.
这对于摄取大量MIML数据所花的时间有很大的影响。
The potential disadvantage is that you cannot use plain SQL to query the MIML data in DB2.
潜在的缺点是，不能使用纯s QL来查询DB 2中的MIML数据。
Also, MIML data shredded into a relational schema is more easily accessible for most BI tools.
而且，对于大多数BI工具而言，分解到关系模式中的MIML数据更易于访问。
You also notice that this schema does not represent all the data items from the original MIML file.
还需注意，这种模式并不表示原始MIML文件中的所有数据项。
For example, all the detailed information about keyword occurrences (MIML element) has been skipped.
例如，所有关于关键词出现情况的详细信息(MIML元素)已经被省略。
The alternative to shredding is to store and index the MIML data in a column of type XML in a DB2 table.
作为分解方法的另一种备选方法是将MIML数据存储在db2表中的xml类型的列中，并为之建立索引。
As an alternative to annotated schema, you can use the SQL function XMLTABLE to shred the MIML documents.
除了使用带注释的模式以外，另一种选择是使用SQL函数XMLTABLE来分解MIML文档。
The first relational schema is a very straightforward relational representation of the MIML data (Figure 5).
第一种关系模式是对MIML数据的非常简单的关系表示(图5)。
After the annotated schema is registered, you can shred the MIML document into the relational target tables.
注册好带注释的模式之后，就可以将MIML文档分解到关系目标表中。
This section USES DB2's annotated schema shredding feature to map MIML data to the simple four-table schema.
本节使用DB 2带注释的模式分解特性将MIML数据映射到简单的4表模式。
A sample stored procedure that shreds MIML data into the refined star schema (Figure 8) is attached to this article.
本文附带了一个示例存储过程，该存储过程将MIML数据分解到改进的星型模式中(图8)。
There are various ways in which you can define a set of relational tables to represent the MIML data in relational format.
可以以多种不同的方式定义一组关系表，以便用关系格式表示MIML数据。
As an alternative to shredding, you can simply use a table with a column of type XML to store, index, and query the MIML data.
作为分解的备选方法，可以简单地使用一个包含xml列的表来存储、索引和查询MIML数据。
The output of natural language processing is another XML file format called Mining Markup language (MIML), as shown in Figure 3.
自然语言处理的输出是另一个被称作MiningMarkupLanguage (MIML)的XML文件格式，如图3所示。
For queries of low or medium complexity, including the ones in the query MIML Data in DB2 section, the query performance is good.
对于复杂度较低或中等的查询，包括查询DB 2中的MIML数据小节中的查询，查询性能很好。
If you take the hit and shred the MIML data to relational table, then you can use plain SQL with relational indexes to analyze the data.
如果您选择将MIML数据分解到关系表，那么可以使用纯s QL和关系索引来分析数据。
If you decide to shred MIML to relational tables, there are different options for the relational target schema as well as for the actual shredding method.
如果决定将MIML分解到关系表，那么对于关系目标模式和实际的分解方法又有不同的选项。
In this comparison, it is important to note that the approach with the refined star schema converts only a subset of the MIML data into relational format.
在这个比较中，注意使用改进的星型模式的方法只是将一部分MIML数据转换成关系格式。
This is because this relational schema requires the generation and proper use of foreign keys, which are key values that are not included in the original MIML.
这是因为这种关系模式要求生成并适当使用外键，而这是原始miml中没有包括的键值。
As mentioned above, the typical flow is for the analysis results (MIML) to be indexed so that users can interactively explore the content using the interactive user interface.
如前所述，典型的流程是为分析结果(MIML)构建索引，以便用户可以使用交互式界面交互式地专研内容。
The DOCUMENT table contains the basic information of each document: the document ID, title, and the document content ("input"). Remember that a MIML document has the following
DOCUMENT表包含每个文档的基本信息：文档ID、标题和文档内容（“input”）。
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