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One Database Pass Algorithms of Mining Top-k Frequent Closed Itemsets

机译:一个数据库通过挖掘Top-K频繁关闭项目集的算法

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The FP-growth algorithm is a powerful algorithm to mine frequent patterns and it is non-candidate generation algorithm using a special structure FP-tree. Many algorithms proposed recently are based on FP-tree. These algorithms include all frequent itemsets mining, closed frequent itemsets mining and top-k closed frequent itemsets mining. However, it still requires two database scans, Although it is not a problem for static database, it is not efficient for frequent pattern mining, interactive and incremental mining. In order to enhance the efficiency of FP-tree based algorithms, propose a novel algorithm called QFPC which can create FP-tree with one database pass. Also propose a novel algorithm PFPTC to create FP-tree parallelly.
机译:FP-Growth算法是频繁模式的强大算法,它是使用特殊结构FP-Tree的非候选生成算法。最近提出的许多算法基于FP-Tree。这些算法包括所有频繁的项目集挖掘,封闭频繁的项目集挖掘和Top-K封闭式频繁项目集采矿。但是,它仍然需要两个数据库扫描,尽管静态数据库不是问题,但对于频繁的模式挖掘,交互和增量挖掘是不高的。为了提高基于FP-Tree的算法的效率,提出一种名为QFPC的新算法,可以使用一个数据库通过创建FP-Tree。还提出了一种新颖的算法PFPTC并行创建FP树。

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