Frequent patterns mining involves mining transactions, sequences, trees and graphs.
频繁模式挖掘的研究对象包括事务、序列、树和图。
Frequent patterns mining is an important aspect of data mining and includes mining transaction, sequence, tree and graph.
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。
A new algorithm, constrain-based frequent patterns mining, was developed to provide frequent pattern mining with constraints.
在频繁模式挖掘过程中能够动态改变约束的算法比较少。
To speed up mining sequential patterns, reducing the time cost is very important during discovering sequential frequent sequence.
提高序列模式挖掘算法效率的关键在于减少发现频繁序列的时间。
An active research in data mining area is the discovery of sequential patterns, which finds all frequent sub-sequences in a sequence database.
数据挖掘领域一个活跃的研究分支就是序列模式的发现，即在序列数据库中找出所有的频繁子序列。
How to generate candidate frequent sequential pattern and calculate its support is a key problem in mining frequent sequential patterns.
如何确定候选频繁序列模式以及如何计算它们的支持数是序列模式挖掘中的两个关键问题。
Mining and updating maximum frequent patterns is a key problem in data mining research.
挖掘和更新最大频繁模式是多种数据挖掘应用中的关键问题。
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。
Mining frequent patterns in transaction databases, time series databases, and many other kinds of databases has been studied popularly in data mining research.
挖掘事务数据库、时间序列数据库中的频繁模式已经成为数据挖掘中很受关注的研究方向。
Mining maximum frequent patterns is a key problem in data mining research.
挖掘最大频繁模式是多种数据挖掘应用中的关键问题。
With the increasing demand of massive structured data analysis, mining frequent subgraph patterns from graph datasets has been an attention-deserving field.
随着对大量结构化数据分析需求的增长，从图集合中挖掘频繁子图模式已经成为数据挖掘领域的研究热点。
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。
Sequential pattern mining, which discovers frequent subsequences as interesting patterns in a sequence database.
序列模式挖掘就是发现序列数据库中的频繁子序列作为用户感兴趣的模式。
It gives the definition of the frequent maximum pattern with constraint and develop an algorithm for mining frequent maximum patterns with convertible anti-monotone constraint.
给出基于约束的频繁最大模式的定义和挖掘基于约束的频繁最大模式算法。
An incremental mining technique is proposed in order to solve the problem of frequent updating of moving log database and mine the user mobility patterns.
该文主要对移动日志数据库不断更新的问题，提出了增量挖掘的方法，挖掘用户的移动模式。
The frequent patterns of texture could be mined by the algorithm of association rules mining. The association rules could be combined to represent the texture.
采用关联规则挖掘算法对图像纹理的频繁模式进行挖掘，通过联合关联规则来表达纹理。
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。
An active research in data mining area is the discovery of sequential patterns, which finds all frequent sub - sequences in a sequence database.
数据挖掘领域的一个活跃分支就是序列模式的发现，即在序列数据库中找出所有的频繁子序列。
When mining such rules, the support threshold can be ignored, so the frequent and infrequent patterns can be produced together.
挖掘这种规则时，可以忽略支持度阈值，因此可同时得到频繁模式和非频繁模式。
Absrtact: An active research in data mining area is the discovery of sequential patterns, which finds all frequent sub - sequences in a sequence database.
摘要：数据挖掘领域一个活跃的研究分支就是序列模式的发现，即在序列数据库中找出所有的频繁子序列。
The mining of frequent closed patterns plays an essential role in association analysis method.
频繁闭合模式挖掘是关联分析的关键步骤。
A music style identification system MSC is introduced. The system bases on music melody mining. The system takes MIDI as data source, mines frequent patterns of different styles...
介绍了一个音乐风格识别系统MSC，系统以MIDI乐曲为数据源提取出乐曲的旋律，对不同风格乐曲的旋律进行了频繁模式的挖掘和对测试乐曲的风格识别。
A music style identification system MSC is introduced. The system bases on music melody mining. The system takes MIDI as data source, mines frequent patterns of different styles...
介绍了一个音乐风格识别系统MSC，系统以MIDI乐曲为数据源提取出乐曲的旋律，对不同风格乐曲的旋律进行了频繁模式的挖掘和对测试乐曲的风格识别。
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