A Skipping FP-tree for Incrementally Intersecting Closed Itemsets in On-Line Stream Mining

被引：4
|
作者：
Nishina, Takumi [1 ]
Iwanuma, Koji [1 ]
Yamamoto, Yoshitaka [1 ]
机构：
[1] Univ Yamanashi, Dept Comp Sci & Engn, Kofu, Yamanashi, Japan
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP) | 2019年
关键词：
data mining; stream; closed itemset; FP-tree; intersection; compression; skip;
D O I：
10.1109/bigcomp.2019.8679296
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
An on-line mining for a data stream consisting of large transactions is still quite difficult because of an explosion of frequent itemsets. In this paper, we propose a new data structure, called a skipping FP-tree, which enables us to effectively compress the set of closed itemsets in a stream. We show, through experimental evaluations, the skipping FP-tree achieves more than ten times faster computation for incremental intersections.
引用
收藏
页码：127 / 130
页数：4
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