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- 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。
- Study of Maximum Frequent Item Sets based on web log mining 基于web挖掘中最大频繁项目集的研究
- Maximum Frequent Item Sets 最大频繁项目集
- maximum frequent item set 最大频繁项目集
- 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。
- 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。
- constrained frequent item sets mining 约束频繁项挖掘
- maximal frequent item set mining 最大频繁项集挖掘
- An Algorithm Mining Frequent Item Set and their Related Transaction Set 频繁项目集及相关事务集的挖掘算法
- An Algorithm of Extract Association Rules form Concept Lattice Based on the Biggest Frequent Item Sets 在概念格上基于最大频繁项集关联规则提取算法
- long frequent item sets 长频繁项目集
- frequent item sets 频繁项集
- maximal frequent item sets 最大频繁项目集
- Discovering maximum frequent itemsets is a key problem in many data mining applications. 发现最大频繁项目集是多种数据开采应用中的关键问题 .
- weighted frequent item sets 加权频繁集
- The Personalize item settings dialogue box appears. 一个私人设置的对话框出现了。
- In this paper，a new kind of algorithms BFI-DMFI（Mining Maximum Frequent Itemsets） and BFI-DCFI（Mining Frequent Closed Itemsets） is proposed. 摘要 提出了基于频繁项集的最大频繁项集（BFI-DMFI）和频繁闭项集挖掘算法（BFI-DCFI）。
- frequent item sets mining 频繁项集挖掘
- In BFI-DMFI，we can confirm whether a frequent itemsets is also a maximum frequent itemsets through detecting whether exiting their superset itemsets in frequent itemsets. BFI-DMFI算法通过逐个检测频繁项集在其集合中是否存在超集确定该项集是不是最大频繁项集；
- The MFIA_VTL algorithm finds maximum frequent itemsets through partitioning itemsets search space based on the prefix in the database with the vertical tid-list of transactions. 该算法针对数据库的垂直事务标识列表结构对项集搜索空间进行基于前缀的划分，来发现最大频繁项集。
