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- Sequential pattern mining, which has broad applications, is one of key research areas in data mining. 摘要序列模式挖掘是数据挖掘中一个重要研究方向，具有广泛的应用背景。
- Sequential pattern mining is useful in various domains, such as customer behavior analysis, economic indices analysis, tax prediction, and fraud detection. 摘要序列样式探勘可应用顾客行为分析、经济指标分析、财税预测、诈欺侦测等领域，以辅助决策制定或针对重要事件进行预测。
- Based on the above algorithm, a FCL based sequential patterns mining algorithm (SECLSP) is implemented. 在此基础上,实现了基于频繁概念格的序列模式发现算法SECLSP。
- closed sequential pattern mining 闭合序列模式挖掘
- sequential pattern mining algorithm 序列模式挖掘算法
- constraint sequential pattern mining 约束序列模式挖掘
- non-neighbouring sequential pattern mining algorithms 非邻近序列模式挖掘算法
- Application of Sequential Pattern Mining to Equipment Anticipatory Maintenance 序列挖掘在设备预维修中的应用
- Item Position Index Based Pattern Growth Method for Sequential Pattern Mining 基于项目位置索引的序贯模式增量挖掘方法
- Sequential Patterns Mining Approach for Network Intrusion Detection 网络入侵检测中序列模式挖掘技术研究
- Efficient sequential pattern mining algorithm based on average value constraint satisfaction pruning strategy 基于均值约束满足度剪枝策略的高效序列模式挖掘算法
- An Incremental Updating Sequential Pattern Mining Algorithm Based on Weight Function 一种基于权值的序列模式更新算法
- Application of Sequential Pattern Mining Algorithm in Alarm Information Processing of Power System 序列模式挖掘在电力系统警报信息处理中的应用
- CSE algorithm:a sequential pattern mining method by extending frequent sequences CSE算法:利用对频繁序列扩展来进行序列模式挖掘
- sequential pattern mining 序列模式挖掘
- Application of Sequential Patterns Mining Project on Electronic Commerce Personal Information Service 序列模式挖掘在电子商务个性化服务中的应用
- Access pattern mining module fulfills the FAP-Mining algorithm. 访问模式挖掘模块实现了本文第四章提出的FAP-Mining算法。
- F.Masseglia,P.Poncelet,M.Teisseire.Incremental Mining of Sequential Patterns in Large Databases. 邹翔;张巍;蔡庆生;王清毅.;大型数据库中的高效序列模式增量更新算法
- In this article，compression method based on frequent sequential pattern is to improve the usability and intelligibility of data mining，discover useful information from among colossal sequence. 摘要 基于频繁序列模式的压缩技术旨在提高数据挖掘结果的可用性和可理解性，从庞大的序列模式中发现有用的知识。
- sequential patterns mining 序列模式挖掘
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