除此之外，算法对频繁模式树中每个节点增加一个位串来存储该项目的前缀项目，以避免在模式扩展的时候频繁的遍历子树。
In addition, we add a bit string to each node in the tree to store the prefix of the items. By using the structure we can avoid repeatedly traversing the sub-tree while expanding the patterns.
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。
Frequent patterns mining is an important aspect of data mining and includes mining transaction, sequence, tree and graph.
提出了一个新的数据库存储结构AF P -树，利用它来挖掘频繁模式。然后利用项目之间的相互关联做出推荐。最后举例说明了此推荐系统的处理过程。
It proposes a new database store structure AFP-Tree for mining frequent patterns, makes recommendations by exploring associations between items, exemplifies the approach on real data.
频繁模式挖掘的研究对象包括事务、序列、树和图。
Frequent patterns mining involves mining transactions, sequences, trees and graphs.
该算法通过对模式树的各种操作简化了对频繁项集的搜索过程。
To make further improvement on the scalability of the algorithm, we make a further study on the pattern tree, and propose a new algorithm called FP-DFS based on the study.
本文以标记有序树作为半结构化数据的数据模型，研究了半结构化数据的树状最大频繁模式挖掘问题。
In this paper, labeled ordered tree is used as the data model of semi structured data, the problem of maximum tree structured frequent pattern mining from semi structured data is studied.
本文以标记有序树作为半结构化数据的数据模型，研究了半结构化数据的树状最大频繁模式挖掘问题。
In this paper, labeled ordered tree is used as the data model of semi structured data, the problem of maximum tree structured frequent pattern mining from semi structured data is studied.
应用推荐