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    • 1. 发明公开
    • Multivariate insight discovery approach
    • Vorgehensweise zur Entdeckung von多元化Einblicken
    • EP3007078A1
    • 2016-04-13
    • EP14004373.8
    • 2014-12-22
    • Business Objects Software Ltd.
    • Moser, Flavia SilvanaMacaulay, Alexander KennedyGosper, Julian
    • G06F17/30
    • G06F17/30592G06F17/30554G06F17/30563G06F17/30572G06T11/206
    • A raw dataset including measures and dimensions is processed, by a preprocessing module, using an algorithm that produces a preprocessed dataset such that at least one type of statistical analysis of the preprocessed dataset yields equal results to the same type of statistical analysis of the raw dataset. The preprocessed dataset is then analyzed by a statistical analysis module to identify subsets of the preprocessed dataset that include a non-random structure or pattern. The analysis of the preprocessed dataset includes the at least one type of statistical analysis that produces the same results for both the preprocessed and raw datasets. The identified subsets are then ranked by a statistical ranker based on the analysis of the preprocessed dataset and a subset is selected for visualization based on the rankings. A visualization module then generates a visualization of the selected identified subset that highlights a non-random structure of the selected subset.
    • 预处理模块使用生成预处理数据集的算法来处理包括度量和尺寸的原始数据集,使得预处理数据集的至少一种类型的统计分析产生与原始数据集的相同类型的统计分析相同的结果 。 然后通过统计分析模块分析预处理数据集,以识别包括非随机结构或模式的预处理数据集的子集。 预处理数据集的分析包括对预处理数据集和原始数据集产生相同结果的至少一种类型的统计分析。 然后,基于预处理数据集的分析,所识别的子集由统计学家排序,并且基于排名选择用于可视化的子集。 然后,可视化模块生成突出显示所选子集的非随机结构的所选确定的子集的可视化。