数据挖掘通常涉及到一些标准的任务，包括聚集、分类、回归分析和关联性规则学习。

Data mining commonly involves a few standard tasks that include clustering, classification, regression, and associated rule learning.

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结论——：我们的数据表明：有选择的阻断血小板粘附和聚集的关键性信号通路，会带来不同的关于卒中后果和出血并发症方面的影响。

Conclusions - : Our data indicate that the selective blockade of key signaling pathways of platelet adhesion and aggregation has a different impact on stroke outcome and bleeding complications.

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在聚类和非一致性数据库无聚集查询基础上提出聚集查询重写方法。

This paper presents the rewriting method for aggregation queries based on clusters and non-aggregation queries in inconsistent databases.

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