Frequent itemsmining is a very basic but important task in the data stream processing.
频繁项集挖掘是一个非常基本的,但最重要的任务,在数据流处理。
2
Many approximation algorithms behave well in frequent itemsmining, but can not control their memory consumption.
许多近似算法能够有效进行频繁项挖掘,但不能有效控制内存资源消耗。
3
A frequent itemsmining algorithm of stream data (SW-COUNT) was proposed, which used data sampling technique to mine frequent items of data flow under sliding Windows.