Description: 序列模式的概念最早是由Agrawal和Srikant 提出的
序列模式定义：给定一个由不同序列组成的集合，其中，每个序列由不同的元素按顺序有序排列，每个元素由不同项目组成，同时给定一个用户指定的最小支持度阈值，序列模式挖掘就是找出所有的频繁子序列，即该子序列在序列集中的出现频率不低于用户指定的最小支持度阈值-sequential pattern is the earliest concept of Agrawal and Srikant from the sequential pattern definitions : given a different set of sequence, in which each sequence by different elements arranged in an orderly sequence, Elements from each different project components, and given a user-specified minimum support threshold, sequential pattern mining is to find all the frequent sequences. that the sequences in the series focus on the frequency of not less than user-specified minimum threshold of support Platform: |
Size: 18715 |
Author:kiki9975 |
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Description: 序列模式的概念最早是由Agrawal和Srikant 提出的
序列模式定义：给定一个由不同序列组成的集合，其中，每个序列由不同的元素按顺序有序排列，每个元素由不同项目组成，同时给定一个用户指定的最小支持度阈值，序列模式挖掘就是找出所有的频繁子序列，即该子序列在序列集中的出现频率不低于用户指定的最小支持度阈值-sequential pattern is the earliest concept of Agrawal and Srikant from the sequential pattern definitions : given a different set of sequence, in which each sequence by different elements arranged in an orderly sequence, Elements from each different project components, and given a user-specified minimum support threshold, sequential pattern mining is to find all the frequent sequences. that the sequences in the series focus on the frequency of not less than user-specified minimum threshold of support Platform: |
Size: 18432 |
Author:kiki9975 |
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Description: 数据挖掘领域一个活跃的研究分支就是序列模式的发现，上传一个prefixspan算法-The field of data mining of an active research branch is the sequential pattern discovery algorithm to upload a PrefixSpan Platform: |
Size: 121856 |
Author:闻晞 |
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Description: 基于候选产生 测试的序列模式挖掘算法，gsp使用序列模式的向下封闭性，采用多次扫描的候选产生测试方法。-Have a test based on a candidate sequential pattern mining algorithm, gsp down the use of closed sequential patterns, and the use of multiple scan generated candidate testing methods. Platform: |
Size: 15360 |
Author:tian |
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Description: GenPrefixSpan算法源码，在PrefixSpan基础上增加了gap限制-GenPrefixSpan algorithm source code, in PrefixSpan based on an increase of gap limit Platform: |
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Author:张中举 |
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Description: 基于改进FP-Tree的序列模式挖掘算法，已经调试通过-Based on Improved FP-Tree of sequential pattern mining algorithms have been debugging through Platform: |
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Author:wanghuaqiu |
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Description: 序列模式挖掘是数据挖掘的一个重要分支，在序列事务及；有关信息处理中有着广泛的应用，如顾客购物习惯、web访问模式、科学实验过程分析、自然灾害预测、疾病治疗、药物检验以及{ sizej pos；
DNA等。序列模式挖掘算法有AprioriAll、GsP、F’reeSpan、本文将设计与实现针对string数据类型的算法，来对序列模式挖掘有更深入的剖析。-Sequence pattern mining is an important branch of data mining, and in the sequence matters the information processing has a wide range of applications, such as customer shopping habits, web access mode, the process of scientific experiments, natural disaster prediction, disease treatment, drug testing, and { sizej pos DNA and so on. Sequential pattern mining algorithm AprioriAll, GsP, F' reeSpan, this paper design and implementation of algorithms for string data types, to sequence pattern mining on a more in-depth analysis. Platform: |
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Author:谢亚妮 |
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Description: 数据挖掘(Data Mining)阶段首先要确定挖掘的任务或目的。数据挖掘的目的就是得出隐藏在数据中的有价值的信息。数据挖掘是一门涉及面很广的交叉学科，包括器学习、数理统计、神经网络、数据库、模式识别、粗糙集、模糊数学等相关技术。它也常被称为“知识发现”。知识发现(KDD)被认为是从数据中发现有用知识的整个过程。数据挖掘被认为是KDD过程中的一个特定步骤，它用专门算法从数据中抽取模式(patter，如数据分类、聚类、关联规则发现或序列模式发现等。数据挖掘主要步骤是：数据准备、数据挖掘、结果的解释评估。-Data Mining (Data Mining) stage must first determine the mission or purpose of the excavation. The purpose of data mining is to draw valuable information hidden in the data. Data mining is an interdisciplinary involving a wide range, including control study, mathematical statistics, neural networks, databases, pattern recognition, rough sets, fuzzy mathematics and other related technologies. It is also often referred to as the " knowledge discovery" . Knowledge discovery (KDD) is that the whole process is to discover useful knowledge from data. Data mining is a particular step in the KDD process, with a special algorithm (patter, such as data classification, clustering, association rules discovery or sequential pattern discovery. Extracted from the data model and data mining major steps: data preparation, data mining, interpretation of the results evaluated. Platform: |
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Author:dlufl |
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Description: Mining sequential pattern is one of the
common data mining task for many real-life
applications.Previous existing algorithm such as
CAMLS(Constraint-based Apriori Algorithm for
Mining Long Sequences) mines the complete set of
frequent sequences(Long) satisfying a min-sup
threshold in a sequence.However,mining long
sequences will generate an explosive number of
frequent sequences, which is prohibitively costly in
both run time and space storage.In this paper, we
propose to improve CAMLS algorithm to produce
only for closed sequences.Instead of mining full set of
sequences,we plan to mine only short(closed)
sequences.i.e.,those containing,no super sequences
with same support.Ou Platform: |
Size: 124928 |
Author:varun |
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Description: 在2006年9月召开的ICDM会议上，邀请了ACM KDD创新大奖(InnovationAward)和
Top 10 Algorithms in Data Mining
IEEEICDM研究贡献奖(Research Contributions Award)的获奖者们来参与数据挖掘10大算
法的选举，每人提名10种他认为最重要的算法-Classification，Statistical Learning，Top 10 Algorithms in Data Mining，materials on Association Analysis，Link Mining，Clustering，Bagging and Boosting，Sequential Patterns，Integrated Mining，Rough Sets，Graph Mining Platform: |
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Author:yz |
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Search - Mining Sequential