这三个类中的每个类都是一个复杂的数据类型，包含用于描述特定平台性质的结构化信息。
Each of these is a complex data type containing structured information describing specific platform qualities.
了解了每个服务实现的复杂性之后，就需要采用一种结构化方法了解应该在SOA项目的什么地方应用数据质量分析。
Given the potential complexity of each service implementation, a structured approach is needed to understand where data quality analysis should be applied in any SOA project.
但是，如果大多数数据更适合采用高度结构化的实体-关系模型，数据不太像文档并且关系更复杂，那么选择NXD可能并不合适。
If, however, the majority of your data fits better in a highly structured entity-relationship model and is less document-like and more intertwined, then choosing an NXD might not help your situation.
更为复杂的问题是，大量需要处理的数据是非结构化或者半结构化的，这就更难查询了。
Further compounding the issue is that a lot of the information needing to be processed is either unstructured or semi-structured text, which is difficult to query.
支持一种用于WebSphereTX的新数据绑定，从而允许在半结构化数据和复杂行业模式之间来回转换业务对象。
A new data binding is supported for WebSphere TX, enabling the transformation of business objects to and from semi-structured data and complex industry schemas.
阐述了以结构化数据和复杂类型数据挖掘为主要内容的信息挖掘技术。
The information mining technology, which includes the structured data and complex structured data mining, is introduced in this paper.
然而由于网页布局设计的复杂性和用户发表帖子的灵活性，从论坛网页中抽取结构化的数据是一项未能很好解决并非常具有挑战性的任务。
Because of both complex page layout designs and unrestricted user created posts, extracting structured data from web forum pages is a very challenging task and not solved well.
可扩展标识语言以其合理的数据组织结构和可扩展的特性，成为各种复杂数据，特别是半结构化数据表示和处理的良好工具。
XML (Extensible Markup Language) is a good tool for representing and processing complex data, especially semistructured data for its reasonable data organization structure and extensibility.
由于网页布局设计的复杂性和用户发表帖子的灵活性，从论坛网页中抽取结构化的数据是一项未能很好解决并非常具有挑战性的任务。
Because of both complex page layout designs and unrestricted user created posts, extracting structured data from Web forum pages is a very challenging task and not easily solved.
传统的数据挖掘方法只能从单一关系中进行模式发现，而很难在复杂的结构化数据中发现复杂的关系模式。
The classical data mining approaches can only look for patterns in single relation, and it is difficult to look for complex relational patterns which involved in multi-relational databases.
用户不需要掌握复杂的结构化查询语言，也无需了解数据模式，只需要输入查询关键词就可以进行数据库的查询。
Users do not have to master the complex query languages; nor do they have to be aware of the database schema. They only need to enter the keywords to perform a database query.
用户不需要掌握复杂的结构化查询语言，也无需了解数据模式，只需要输入查询关键词就可以进行数据库的查询。
Users do not have to master the complex query languages; nor do they have to be aware of the database schema. They only need to enter the keywords to perform a database query.
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