Abstract:
This paper proposes an algorithm of Mining Frequent closed itemsets with Window Sliding Rapidly(MFWSR) against the complexity of data structure and process for determination. With the data stream represented by compact data structure, process for determination simplified, MFWSR improves the temporal and spatial efficiency while it can response to the requests of user-specified support threshold. Experimental results show that compared with existing algorithms, MFWSR achieves higher temporary and spatial efficiency while the accuracy remains.
Key words:
data stream,
data mining,
frequent closed itemsets
摘要: 针对频繁闭项集挖掘算法中数据结构与处理机制复杂的问题,提出窗口快速滑动的数据流频繁闭项集挖掘算法——MFWSR。算法通过采用紧致的数据结构和简化的判断过程提高时空效率,支持响应不同用户支持度阈值的查询。实验结果表明,在保持已有算法精度的情况下,MFWSR具有更高的时空效率。
关键词:
数据流,
数据挖掘,
频繁闭项集
CLC Number:
DAO Ke, WANG Yi-Ji. Algorithm of Mining Frequent Closed Itemsets on Data Streams[J]. Computer Engineering, 2010, 36(18): 49-51.
陶克, 王意洁. 数据流上的频繁闭项集挖掘算法[J]. 计算机工程, 2010, 36(18): 49-51.