这种隐式关联避免了数据库表连接和额外的字段选择，降低了数据传输的大小。
This implicit association avoids database table joins and extra selections, and cuts down data transfer size.
更改此关系的惟一方式是丢弃此表并在与不同的数据库分区组相关联的一个不同的表空间内重新创建它。
The only way to change this relationship is to drop the table and recreate it in a different table space that is tied to a different database partition group.
为了解决这些问题，本文介绍了关联分析在嵌入式移动数据库上的实现过程。
In order to solve the question, this paper introduce process of realization of association in embedded mobile database.
数据隐私问题引起人们的广泛关注，如何在分布式数据库的环境下挖掘关联规则成为研究的热点。
With the growing concern over data privacy-preserving problem, how to discover association rules from distributed databases becomes one of the hot topics of this field.
FSES引入数据库关联技术，结合传统的产生式规则法和框架法等人工智能技术，建立了以关系型知识库为主的农业生态系统知识库体系。
The FSES adopted relation database system and interrelated knowledge presentation technology in combination with production rule and frame system. An uncompleted fuzzy reasoning was applied in FSES.
本文的研究工作主要包括以下两个方面：一方面，提出了基于数据库变化的关联规则增量式更新算法。
The work of author mainly focuses on two aspects in the following:On one hand, an incremental updating algorithm for mining association rules based on the change of database is proposed.
本文的研究工作主要包括以下两个方面：一方面，提出了基于数据库变化的关联规则增量式更新算法。
The work of author mainly focuses on two aspects in the following:On one hand, an incremental updating algorithm for mining association rules based on the change of database is proposed.
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