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Efficient Mining of Frequent Closed XML Query Pattern

机译:频繁关闭XML查询模式的有效挖掘

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Previous research works have presented convincing arguments that a frequent pattern mining algorithm should not mine all frequent but only the closed ones because the latter leads to not only more compact yet complete result set but also better efficiency. Upon discovery of frequent closed XML query patterns, indexing and caching can be effectively adopted for query performance enhancement. Most of the previous algorithms for finding frequent patterns basically introduced a straightforward generate-and-test strategy. In this paper, we present SOLARIA~*, an efficient algorithm for mining frequent closed XML query patterns without candidate maintenance and costly tree-containment checking. Efficient algorithm of sequence mining is involved in discovering frequent tree-structured patterns, which aims at replacing expensive containment testing with cheap parent-child checking in sequences. SOLARIA~* deeply prunes unrelated search space for frequent pattern enumeration by parent-child relationship constraint. By a thorough experimental study on various real-life data, we demonstrate the efficiency and scalability of SOLARIA~* over the previous known alternative. SOLARIA~* is also linearly scalable in terms of XML queries' size.
机译:先前的研究工作提出了令人信服的论点,即频繁模式挖掘算法不应该对所有频繁算法进行挖掘,而应仅对封闭算法进行挖掘,因为封闭算法不仅可以使结果集更紧凑,更完整,而且可以提高效率。一旦发现频繁关闭的XML查询模式,就可以有效地采用索引和缓存来增强查询性能。以前,大多数用于查找频繁模式的算法基本上都引入了一种简单的生成和测试策略。在本文中,我们提出了SOLARIA〜*,这是一种用于挖掘频繁关闭的XML查询模式的有效算法,而无需进行候选维护和昂贵的树包含检查。高效的序列挖掘算法涉及发现频繁的树状结构模式,该模式旨在用序列中的便宜父子检查代替昂贵的遏制测试。 SOLARIA〜*通过父子关系约束来深度修剪无关的搜索空间以进行频繁的模式枚举。通过对各种现实数据的全面实验研究,我们证明了SOLARIA〜*优于以前的已知替代方法的效率和可扩展性。就XML查询的大小而言,SOLARIA〜*也可以线性扩展。

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