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- 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。
- Our algorithm, HATS, uses a tree to maintain potential candidate sequential patterns in each sequence parallelly. 我们的演算法简称为HATS，运用树状结构代表每一个序列中的循序元素。
- 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
- DMGSP algorithm compresses local frequent sequential patterns into a lexicographic sequence tree, and avoids translation of repeated prefixes. 该算法将分布式环境下的各站点得到的局部序列模式压缩到一种语法序列树上，避免了重复的序列前缀传输。
- 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。
- And the veracity of prefetching is high on normal access patterns such as sequential pattern and strided pattern. 该机制根据访问模式的变化在动态PBL算法和ISG算法之间切换，对常见的访问模式如顺序和跨度访问模式都可以进行较为正确的预取。
- 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。
- In this paper,we introduce some tipical algorithms for discovering all significant sequential pattern over a large database of transactions, and compare their tradeoffs. 本文介绍几种开采大型事务数据库中时序模式的几个典型算法;并对它们的效率进行比较分析.
- 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。
- 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. 数据库中知识发现(Knowledge Discovery in Database，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。
- The core idea of this algorithm was to compress local frequent sequential patterns into the corresponding lexicographic sequence tree so as to avoid transmission of repeated prefixes. 该算法将各站点得到的局部序列模式压缩到一种语法序列树上，避免了重复的序列前缀传输；
- For the phase of sequential pattern discovery，the paper presented the classic Apriori and the FS algorithms and proposed a new AFS algorithm which can avoid the demerit of FS algorithm. 对于序列模式挖掘，本文详细介绍了适用于Web日志频繁访问路径挖掘的类Apriori算法和FS算法，并对FS算法的不足进行了改进，提出了AFS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。
- multi-dimensional sequential pattern 多维序列模式
- closed sequential pattern mining 闭合序列模式挖掘
- maximal frequent sequential pattern 最大频繁序列模式
- Top-k Closed Sequential Pattern(Topk_CSP) Top-k闭序列模式
- sequential pattern mining algorithm 序列模式挖掘算法
- This cloth has a pattern of blue and white squares. 这种布有蓝白格子的图案。
- constraint sequential pattern mining 约束序列模式挖掘
