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- Association rule mining is an important task of data mining. 关联规则是数据开采的重要研究内容 .
- Although the values are numeric, association rules mining requires the values to be categorical. 虽然都是整型值,关联规则挖掘要求值是无条件的。
- Authors propose association rules mining approach based on iceberg queries for analyzing the corelation between net flow and each IP address, and acquire quite good results. 作者采用基于冰山查询的关联规则挖掘方法,对网络流量与各IP之间的联系进行关联分析,取得了较好的效果。
- This paper firstly presents a power set-based association rules mining algorithm which uses pow er set as an association rules mining tool. 首次提出了利用幂集作为挖掘关联规则的工具,给出了基于幂集的关联规则挖掘算法。
- A set of fuzzy association rules mined from the networ... 最后,文中利用遗传算法优化模糊成员函数来选择其参数。
- Fpmine-SPF algorithm has a far taster speed in association rules mining than the widely used Apriori algorithm and has wonderful scalability. Fpmine-SPF算法挖掘关联规则的速度远快于较长期以来广泛使用的Apriori算法，并有相当好的可伸缩性。
- By making a survey of the theories and approaches, we proposed the iFP-Growth algorithm for the association rules mining for the web content data. 本文总结了多种从Web页面中提取半结构化数据的理论与方法，针对Web内容数据的特点，提出的增量式挖掘方法iFP-Growth，使传统的FP-Growth方法适应于动态数据环境的关联规则挖掘。
- Data mining is a new technology to mine valuable informatin from abundant data, and association rules mining is a method of data mining. 数据挖掘就是从大量数据中获取有用信息的一门新技术，关联规则挖掘是数据挖掘方法中的一种。
- Finally a summary and an expectation are made for the method integrating the SVM with ATMS-based association rules mining. 最后对这种集成了支持向量机和关联规则挖掘的技术做了总结和展望。
- This paper elaborates on the process of the design and development of association rules mining system based on Apriori . 随着大量数据不停地收集和存储，许多业界人士对于从他们的数据库中挖掘关联规则越来越感兴趣。
- Association rule mining is an important problem in data mining and KDD, which has been researched widely. 关联规则挖掘是数据挖掘和知识发现中的一个重要问题,自提出以来得到了广泛的研究。
- The date-set are managed equally and conformably in the traditional association rule mining algorithm. 传统的关联规则挖掘算法对更新的数据集按平等一致的方式加以处理。
- Association Rule Mining is an important branch of data mining, and becomes one of the widest applied data mining styles. 关联规则采掘是数据采掘中的一个重要分支，也是目前应用最广泛的一种数据采掘类型。
- Section3 introduces the Association rules mining, analyzes the Apriori algorithm, and explains the implementation of Association rules mining in EDWP-Miner in detail. 第三章介绍了关联规则的研究，分析了Apriori算法，详细阐述了EDWP-Miner中关联规则挖掘的、实现过程。
- Then, the algorithms of association rule mining is discussed, covering issues from Apriori algorithm to its improved algorithms. 然后,对关联规则挖掘算法做了深入的研究,分析总结了关联规则中经典的Apriori算法及其改进算法。
- Association rules mining is an important technique in data mining and KDD, but some problems exist in the association riles mining based on support and confidence. 摘要关联规则挖掘是数据挖掘和知识发现中一门重要技术，但基于支持度-置信度框架的关联规则挖掘存在一些问题。
- Next, after near 10 years research and development, the most essential phase in association rules mining, frequent pattern acquirement, and its techniques have been improved dramatically. 其次，在经历了近10年的发展以后，关联规则挖掘中至关重要的频繁模式获取技术得到了很大的发展。
- The paper focus on the Apriori association rules mining algorithm ,presents an enhanced method which can effectively reduce the number of data to improve the original Apriori algorithm performance. 对Apriori关联规则挖掘算法提出了一种改进方法，使其可以有效地压缩数据规模，提高了原Apriori算法的执行效率。
- In order to improve the trustiness and accuracy of association rules mining, the association rules mining is reduced to the multi-step decision process, and an optimal strategy is proposed based on dynamic programming. 摘要为了得到准确可信任的关联规则，将关联规则的发现归纳为多阶段决策问题，利用动态规划方法对关联规则发现进行优化分析。
- This paper also discusses how to set the optimal minimum support for the common association rules mining algorithm,which can guarantee the frequent items are the weighted frequent items' superset. 同时,给出了最优的最小支持度设定方法,保证了普通关联规则算法所产生的频繁集为加权频繁集的超集。
