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Mining multi-level time-interval sequential patterns in sequence databases

机译:在序列数据库中挖掘多级时间间隔顺序模式

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Mining sequential patterns is an important issue in data mining and has many applications. An extended work of sequential pattern mining, called time-interval sequential pattern mining, is proposed to retrieve time-interval information between successive items. However, previous work only considers single-level time-interval in pattern extraction, which means sequential patterns with cross-level time-intervals are completely ignored. Therefore, this study first defines multi-level time-interval sequential patterns and then presents a novel algorithm, named MLTI-PrefixSpan, for discovering the complete set of multi-level time-interval sequential patterns. Experimental results show that the proposed algorithm is effective on the test dataset.
机译:挖掘顺序模式是数据挖掘中的重要问题,并具有许多应用程序。提出了一种扩展的顺序模式挖掘工作,称为时间间隔顺序模式挖掘,以检索连续项之间的时间间隔信息。但是,以前的工作仅在模式提取中考虑了单级时间间隔,这意味着具有跨级时间间隔的顺序模式将被完全忽略。因此,本研究首先定义了多级时间间隔顺序模式,然后提出了一种新颖的算法MLTI-PrefixSpan,用于发现多级时间间隔顺序模式的完整集合。实验结果表明,该算法对测试数据集有效。

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