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A FP-Tree-Based Method for Inverse Frequent Set Mining

机译:基于FP树的逆频繁集挖掘方法

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摘要

Recently, the inverse frequent set mining problem has received more attention because of its important applications in different privacy preserving data sharing contexts. Several studies were reported to probe the NP-complete problem of inverse frequent set mining. However, it is still an open problem that whether there are reasonably efficient search strategies to find a compatible data set in practice. In this paper, we propose a FP-tree-based method for the inverse problem. Compared with previous "generation-and-test" methods, our method is a zero trace back algorithm, which saves huge computational costs. Furthermore, our algorithm provides a good heuristic search strategy to rapidly find a FP-tree, leading to rapidly finding the compatible databases. More importantly, our method can find a set of compatible databases instead of finding only one compatible database in previous methods.
机译:近年来,逆频繁集挖掘问题因其在不同隐私保护数据共享环境中的重要应用而受到越来越多的关注。据报道,有几项研究探讨了逆频繁集挖掘的NP完全问题。但是,在实践中是否存在合理有效的搜索策略来查找兼容数据集仍然是一个未解决的问题。在本文中,我们针对反问题提出了一种基于FP树的方法。与以前的“生成和测试”方法相比,我们的方法是一种零追溯算法,节省了巨大的计算成本。此外,我们的算法提供了一种很好的启发式搜索策略,可以快速找到FP树,从而快速找到兼容的数据库。更重要的是,我们的方法可以找到一组兼容的数据库,而不是以前的方法中仅找到一个兼容的数据库。

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