序列模式

CRM中序列模式分析与神经网络结合的应用研究

Research of application of combination of sequence pattern analysis and neural network in CRM

序列模式挖掘在Web点击流分析、自然灾害预测、DNA和蛋白质序列模式发现等领域有着广泛应用。

Sequence pattern mining has broad applications in the analysis of Web click streams , the prediction of disasters and the pattern discovery of DNA and protein sequences .

序列模式挖掘算法在Web挖掘上的应用

Application of the Algorithm for Sequential Pattern Mining in Web Mining

基于Web日志的序列模式挖掘应用研究

Research and application of sequential pattern mining based on Web logs

Web日志中序列模式挖掘及其应用

Sequential Patterns Mining and Application in Web Log

提出了一种加权的Web挖掘技术，从Web日志中发现语义限定的加权序列模式。

This paper attempts to propose a weighted Web mining technique using linguistic parameters to discover weighted browsing patterns from log data in Web servers .

K-Means聚类中序列模式和批量模式的比较研究

Research on Comparing the Sequential Learning with Batch Learning for K - Means

这些问题分别涉及频繁序列模式挖掘，Web用户行为特征相似性／差别的量化方法，以及支持Web站点设计优化的数据挖掘技术。

The investigated issues are related with frequent sequential-pattern mining , methods for measuring the differences between two user behaviors , and the data mining techniques for optimizing web-site design .

频繁序列模式挖掘算法Apriori的分析及改进

Analysis and Improved of frequent sequence mining algorithm Apriori

基于序列模式的关联规则Apriori算法的研究与优化

The Studying And Optimizing Of Association Rules Apriori algorithm Based On Sequential Patterns

GNUPATTERN：基于SPLASH算法的开源生物序列模式识别程序

GNU PATTERN : Open Source Pattern Hunter for Biological Sequences Based on SPLASH Algorithm

GSP算法和PSP算法是序列模式挖掘问题的两个主要算法。

The GSP algorithm and the PSP algorithm is the main two algorithms .

论文首先对序列模式挖掘的经典挖掘算法和研究现状进行了深入调查分析，讨论了序列模式挖掘算法用于Web挖掘存在的问题。

Firstly , the thesis gives a deep analysis to the classical sequence pattern mining algorithm and its research status , and also discusses the problems when they are used to mine web sequence patterns .

本文提出了一个基于序列模式挖掘的个性化技术，它使用概念格（conceptlattice）作为存储频繁序列的数据结构。

In this paper we present an sequential-pattern-based recommendation System , which extract usage patterns from web log file and use the concept lattice as its data structure storing frequent sequences .

然而有时还会出现以下情况，顾客在购买了商品A之后，往往不会买商品C，这条规则记为A？？C，这就是序列模式的负关联规则。

But , sometimes customers buy merchandise A , tend not to buy C , this rule is denoted as A ?? C , we call it negative association rules based on sequential patterns .

是N1V的N2是现代汉语中常见的语法序列模式，其内部的结构关系、语义关系十分复杂。

The syntactic structure and semantic relationship is complicated in the pattern of " shi N_1V de N_2 " .

使用一种树形结构来存储挖掘得到的Web访问序列模式，在该树形结构的基础上进行页面匹配，给出了一种基于访问序列模式的页面推荐算法。

Web access sequential patterns are stored via a type of tree structure and the page matching is based on the tree structure . Then , the page recommendation algorithm based on access sequential pattern is proposed .

GSP的引入是为了发现满足序列模式中的时间约束、滑动窗口的模式。GSP算法增加了时间约束、滑动窗口和分类法。

The introducing of GSP is to discover the patterns within the time constrains , sliding windows .

WebLog访问序列模式挖掘

Mining Access Sequential Pattern from WebLog

概念格扩展模型（ECL）适用于挖掘包括序列模式在内的各种知识。

The Extended model of Concept Lattice ( ECL ) is suitable to discover various knowledge including sequential patterns .

会话流中Top-k闭序列模式的挖掘

Top-k Closed Sequential Pattern Mining in Session Streams

但是，与Teradata连接器不同，它只在序列模式下运行。

However , unlike the Teradata connector , it only runs in sequential mode .

数据库中知识发现（KnowledgeDiscoveryindatabase，简称KDD）是当前涉及人工智能和数据库等学科的一门相当活跃的研究领域，序列模式的发现是其中的一个重要研究课题。

Knowledge discovery in database ( KDD ) is a rapidly emerging research field relevant to artificial intelligence and database system , and discovery of sequential patterns is an important field in the KDD research .

序列模式挖掘算法多是利用了关联规则挖掘中的Apriori特性。

Most of the Sequence Pattern Mining ( SPM ) algorithm are using the Apriori characteristic of Association Rule Mining ( ARM ) .

数据预处理是Web使用挖掘的一个关键环节，其结果直接影响到后续的事务识别、路径分析、关联规则挖掘和序列模式挖掘的结果。

Data Preprocessing is a critical step in web usage mining . The results of Data Preprocessing is relevant to the next steps , such as transaction identification , path analysis , association rules mining , sequential patterns mining , and so forth .

比如，序列模式挖掘在商业领域中被网站用来进行用户访问模式挖掘，网络超市用这个技术来进行用户购买行为预测等，生物学家用它来进行生物DNA序列挖掘等。

For example , sequential pattern mining is used for user access pattern mining in the commercial field . Supermarkets managers use this technology for user purchase behavior prediction . Biologists use it to find DNA sequences and so on .

此作业只能在DataStage指导者节点上以序列模式运行，并且它适合于小量数据提取。

This job can run only in sequential mode on the DataStage conductor node and it is suited for small data extraction .

研究了利用GM（1,1）模型发现时间序列模式的方法，用GM（1,1）模型可以从时间序列中寻找变化规律，预测将来的发展趋势。

Investigates a method of time series model with grey system model . Rules in time series can be found by GM ( 1,1 ) model and the trend of the time series can be forecasted .

一种高效的序列模式增量挖掘算法（NPSP）

An Efficient Algorithm with Incremental Data Mining for Mining Sequential Pattern ( NPSP )

系统的数据挖掘模块应用了序列模式挖掘中的GSP算法，并对其进行了改进，引入了主属性及兴趣度。

The main attribute and interest measure are introduced to improve the ( GSP ) algorithm , which is then applied in the data mining module of the system .