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- 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。
- maximal frequent item sequence sets 最大频繁项目序列集
- maximal frequent item set mining 最大频繁项集挖掘
- Improvement of ISS_DM algorithm based on mining of maximal frequent item sequence sets 基于最大频繁项目序列集挖掘ISS_DM算法的改进
- Maximal Frequent Item 最大频繁项集
- maximal frequent item sets 最大频繁项目集
- The limitlessness and mobility of data streams made the traditional frequent item algorithm difficult to apply to data streams. 摘要数据流的无限性和流动性使得传统的频繁项挖掘算法难以适用。
- 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。
- 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。
- Another is that sorting frequent item of not fuzzy attributes in descending order of their support firstly,then sorting database fuzzy attributes with frequent item in ascending order of their nodes number in FFP tree. 先对非模糊属性下的频繁项目按支持度从大到小进行排序,再对模糊属性按其在FFP-树中包含的不同结点的个数,从少到多进行排序,然后依次将各属性下的频繁项目插入到头表中。
- This algorithm can generate new candidate item sets effectively using the frequent item sets in the knowledge database, so it can avoid the problem that candidate item sets is very large. 该算法可以有效利用知识数据库中保留的最小非高频项目集来产生新的候选项目集,避免了候选项目集的数量太庞大的问题。
- For reducing the spaces of rule database and facilitating users to query,the minimal prediction set is used and mined using maximum frequent item sets which are found by a set-enumeration tree. 为缩减关联规则存储空间和方便查询关联规则,提出一种前件为单一项目的最小预测集算法。
- Maximal Frequent Path (MFP) method 最大频繁访问路径方法
- maximal frequent patterns itemsets 最大频繁集
- maximal frequent sequential pattern 最大频繁序列模式
- Thinking about the amount of hits on homepage, this paper improves the algorithm of finding frequent items. 并结合网页特点,考虑到主页的点击率的影响,对生成频繁访问浏览页的算法做了改进;
- weighted maximal frequent subgraph 最大加权频繁子图
- The results show that the algorithm will find a passel of frequent items within a few generations. 实际计算结果表明,该方法一般在几代内即可找到一批长频繁模式。
- maximal frequent closed itemsets 最大频繁闭项目集