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Research of mining algorithms for uncertain spatio-temporal co-occurrence pattern

机译:不确定时空共现模式的挖掘算法研究

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Spatial Co-location pattern mining and Spatio-temporal Co-occurrence pattern mining are important directions of spatial data mining. However, the existing relevant mining algorithms are computational expensive and the algorithms can't effectively deal with uncertain data which are wide spread in many areas. The fast co-occurrence data mining algorithms for the uncertain data are proposed by using the filter-refine method and efficient pruning strategy. The correctness, completeness and complexity of the proposed algorithms are analyzed, and the experimental data shows that the algorithms are effective and reasonable.
机译:空间共置模式挖掘和时空共现模式挖掘是空间数据挖掘的重要方向。然而,现有的相关挖掘算法在计算上是昂贵的,并且该算法不能有效地处理在许多领域中广泛分布的不确定数据。利用滤波细化方法和有效的修剪策略,提出了不确定数据的快速共现数据挖掘算法。对所提算法的正确性,完整性和复杂性进行了分析,实验数据表明该算法是有效,合理的。

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