data streams mining

基本解释

Clustering is an important task in mining evolving data streams.
聚类是挖掘数据流的一种重要工具。
The conventional method can not cluster on the basis of the characteristics of spatial data streams in the data mining process.
空间数据库中存储了海量的实时数据，常规的算法在数据挖掘过程中无法根据空间数据流的特征进行聚类。
By analyzing data streams outliers mining situation of foreign and domain, we found that there exist many problems in the previous algorithms for detecting outliers.
对国内外数据流离群数据挖掘研究情况分析可知，以往的挖掘算法还存在诸多问题。

数据流挖掘
How to make accurately outlier detection in real-time to data in these scenes and achieve the relevant application requirements has become a hot research topic in data streams mining.
如何对这些场景中大量的数据流实时准确地进行异常检测以达到相关的应用需求已成为当前数据流挖掘的研究热点。