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- maximal frequent patterns itemsets 最大频繁集
- maximal frequent pattern 最大频繁模式
- maximal frequent patterns 最大频繁模式
- maximal frequent sequential pattern 最大频繁序列模式
- Using frequent pattern tree,it divides and rules the alarms during the clustering process. 然后举例说明了利用该算法进行聚类的过程。
- Results of the analysis performed on the editorials indicated that the most frequent pattern pertaining to all the studied newspapers was LFV. “一样的花费,更好的质量和服务”,这是新华翻译社对客户的承诺。
- By utilizing the byte characteristic, DFMfi can optimize the mapping and unifying operations on the item sets. Moreover, for the first time a method based on bitmap which uses local maximal frequent item sets for fast superset checking is employed. 算法DFMfi充分利用位图的字节特性,优化了项集的匹配和合并操作,并首次在其中引入了基于局部最大频繁项集的超集存在判断方法。
- In order to overcome the disadvantage of low efficiency of KM-AOI algorithm,an AOI clustering algorithm based on frequent pattern tree is presented. 为了克服KM-AOI算法聚类效率较低的缺点,提出了基于频繁模式树的AOI聚类算法,即在聚类过程中借助频繁模式树,采取分而治之的策略处理警报集以得到规则。
- Secondly,weighted maximal frequent subgraph is defined,which can not only discover important maximal subgraph,but also inherit the property of anti-monotony.Thus,the speed of pruning is quickened. 其次,给出了加权最大频繁子图的定义,不仅可以找出较为重要的最大频繁子图,而且可以使挖掘结果同样具有反单调性,从而可加速剪枝。
- This paper presents ESEquivPS extension support equivalency pruning strategy, a new search space pruning strategy for mining maximal frequent itemsets to effectively reduce the search space. 为了有效地削减搜索空间,提出了一种新的最大频繁项集挖掘中的搜索空间剪枝策略。
- In addition, FPMFI also compresses the conditional FP-Tree (frequent pattern tree) greatly by deleting the redundant information, which can reduce the cost of accessing the tree. 另外;算法FPMFI通过删除FP子树(conditional frequent pattern tree)的冗余信息;有效地压缩了 FP 子树的规模;减少了遍历的开销.
- The characteristics of effective access sequence in the actual application are analyzed and an efficient algorithm OUS based bottom-up strategy is proposed for mining maximal frequent itemsets. 分析实际应用中有效访问序列的特点,提出了一种采用自底向上策略快速挖掘最大频繁项集的OUS算法。
- Then, this paper proposed an increment update algorithm TW-CFI based on frequent pattern trees and sliding windows.This algorithm adapted the characteristics of data streams. 然后,基于频繁模式树,结合滑动窗口技术提出了一种增量更新算法TW-CFI,它能适应数据流的特点并且可以挖掘数据流频繁闭项集信息。
- Furthermore, we present two pattern sanitization algorithms for blocking inference channels in frequent pattern sharing, and evaluate their performance in the experiments. 然后,基于模式净化的思路,提出了两个推理控制算法,并通过实验对算法的性能进行了比较分析。
- Since it lays groundwork for other problem and its intrinsic complexity, the algorithm for frequent pattern miming has become the focus of many research workers. 由于问题本身的基础性和内在复杂性,频繁模式挖掘方法成为许多研究者关注的课题。本文对频繁模式挖掘相关技术进行了研究。
- Maximal Frequent Path (MFP) method 最大频繁访问路径方法
- maximal frequent item sequence sets 最大频繁项目序列集
- 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。
- maximal frequent item set mining 最大频繁项集挖掘
- weighted maximal frequent subgraph 最大加权频繁子图