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.
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.
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.
本文从并行数据库系统的体系结构、并行数据库的查询，聚集，排序及数据可靠性等方面入手，阐述了对并行数据库的认识和看法。
This paper discusses the understanding on the parallel database from the architecture of parallel database systems, parallel database query, aggregation, sorting, and data reliability.
方向数据的聚类分析法对与疾病的时间聚集性进行分析、季节分层分类等有极其重要的意义。
Cluster analysis of directional data is important to temporal clustering analysis of disease and stratification of season.
方向数据的聚类分析法对与疾病的时间聚集性进行分析、季节分层分类等有极其重要的意义。
Cluster analysis of directional data is important to temporal clustering analysis of disease and stratification of season.
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