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PREFIX-PROJECTION Global Constraint for Sequential Pattern Mining

机译:用于顺序模式挖掘的PREFIX-PROJECTION全局约束

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摘要

Sequential pattern mining under constraints is a challenging data mining task. Many efficient ad hoc methods have been developed for mining sequential patterns, but they are all suffering from a lack of genericity. Recent works have investigated Constraint Programming (CP) methods, but they are not still effective because of their encoding. In this paper, we propose a global constraint based on the projected databases principle which remedies to this drawback. Experiments show that our approach clearly outperforms CP approaches and competes well with ad hoc methods on large datasets.
机译:在约束条件下进行顺序模式挖掘是一项艰巨的数据挖掘任务。已经开发出许多有效的临时方法来挖掘顺序模式,但是它们都缺乏通用性。最近的工作已经研究了约束编程(CP)方法,但是由于其编码,它们仍然无效。在本文中,我们提出了基于投影数据库原理的全局约束,以弥补这一缺陷。实验表明,我们的方法明显优于CP方法,并且在大型数据集上可与ad hoc方法竞争良好。

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