The B-Tree Scanner improves transaction processing for logged databases when rows are deleted from a table with indexes.
从有索引的表中删除行时，B -TreeScanner有助于改进启用了日志的数据库的事务处理。
A business transaction is set up by building a directory structure (tree), using these correlators.
事务可以用这些correlator建立目录结构或者树结构。
The MFP algorithm can convert a transaction database into a MFP tree through scanning the database only once, and then do the mining of the tree.
MFP算法能在一次扫描事务数据库过程中，把该数据库转换成MFP树，然后对MFP树进行关联规则挖掘。
Frequent patterns mining is an important aspect of data mining and includes mining transaction, sequence, tree and graph.
频繁模式挖掘是数据挖掘领域的一个重要方面，研究内容一般包括事务、序列、树和图。
This algorithm establish transaction-tree which is based on transaction database create frequent itemsetby backdate reversely from leaf nodes.
此算法主要利用事务数据库建立事务树的方法，由叶子结点反向回溯，导出频繁集。
This algorithm establish transaction-tree which is based on transaction database create frequent itemsetby backdate reversely from leaf nodes.
此算法主要利用事务数据库建立事务树的方法，由叶子结点反向回溯，导出频繁集。
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