Sequence pattern discovery method is used to build behavioral churn model , by which we can distinguish the typical behavioral sequences of the churned customers and predict present customers " churn tendency 客户流失的行为模型采用序列模式发现方法，识别出流失客户的典型行为序列，用作流失趋势的预测。
In this dissertation , we study the similar time series search , and present the method to retrieve the similar sequences which have the approximately similar pattern instead of only those which have the same value 时间序列挖掘包括规则发现、周期模式挖掘、序列模式挖掘和相似性查询，其中，时间序列的相似性查询是时间序列挖掘的一个重要方面。
The fuzzy distance is defined to measure the similarity of two elements , and the similarity distance of two sequences is defined as the mean of the fuzzy distance of the elements on the mapping path 2为了度量序列模式的相似性，定义了顺序映射来描述序列变化模式之间的对齐，将序列映射路径上的模糊相似性距离作为两个序列之间的相似性度量。
According to the theory , the brain is able to discriminate between , say , a chair and a table because each of them will generate a distinct sequence of patterns within the neural system that the brain then interprets 根据这个理论的观点，大脑能够分辨出椅子和桌子是因为它们在神经系统里产生出两种完全不同的信号序列模式，然后大脑再对之进行诠释。
Then we introduce pcws in details and use this model to carry on the log pretreatment , users discern , conversation discerns , find user ' s route and recognizing sequence - pattern . finally the result of the experiment is evaluate 最后,具体介绍了利用该模型进行日志文件预处理,用户识别,会话识别,挖掘用户路径和序列模式识别的方法,并给出试验结果。
The current research of time series are focus on the finding of the knowledge between the events in the single time series , for example trend , sequential patterns , finding similitude patterns , association rules , finding period , etc 当前对时间序列的研究集中在单一时间序列内部关系的发现如：趋势、序列模式、相似性模式的搜索，关联规则、周期的发现等等。
And then , a extent of association rules - time series pattern is discussed , and an efficient improved algorithm of web mining is presented . the performance of algorithms is verified on the basis of synthetic data too 然后论文介绍了关联规则的一种扩展?时间序列模式挖掘方面的算法，给出了web日志文件挖掘的高效、新颖的改进算法，并用实验验证了此种方法的有效性。
This tool is centered on the user , under the user " s control , and to be capable to effectively mine the rule of time sequence model and the classification rule and the association rule in the database or data warehouse 设计并初步实现了一个数据挖掘原型系统，该工具以用户为中心，在用户的干预下能够有效的对现实数据库、数据仓库进行时间序列模式、分类规则和关联规则的挖掘。
This thesis discussed two important topics in the biological sequence analysis . safss and data mining method for protein secondary structure prediction are of importance , which lay the foundation for the further research for author 本文的研究内容是生物序列分析中两个重要课题,研究中提出的safss比对方法和基于序列模式挖掘的蛋白质二级结构预测方法具有一定的研究意义,为作者进一步进行序列分析研究奠定了基础。
Also , some of data mining algorithms that are commonly used in web usage mining are clustering , association rule generation , sequential pattern generation etc . clustering analysis allows one to group together users or data items that have similar characteristics 同时本篇论文也主要提出了一些经常被使用的数据挖掘的算法像聚类挖掘、关联规则挖掘、序列模式挖掘等。聚类挖掘是将具有相同属性的用户或数据项聚在一起成为一类。
