According to the complexity of pattern, the mined characteristic patterns could be sorted as frequent item, frequent sequence and frequent sub tree, etc.
根据特征模式复杂性，可分为频繁项模式、频繁序列模式以及频繁子树模式等。
This paper proposes a fast algorithm DMFP and an updating algorithm IUMFP, which are based on Prefix Tree for mining maximum frequent patterns.
因此，文章提出了一种最大频繁模式的快速挖掘算法DMFP及更新算法IUMFP。
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。
The paper builds tree-model of RNA molecules and utilizes frequent sub tree mining algorithm to mine common topological patterns among RNA secondary structures.
本文对RNA分子建立树形模型，利用频繁子树挖掘算法挖掘RNA二级结构中的公共拓扑模式。
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.
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.
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。
应用推荐