计算机工程与应用2011，Vol.47Issue(20)：121-125,5.DOI:10.3778/j.issn.1002-8331.2011.20.035
不确定数据频繁项集挖掘方法综述
Survey on algorithm of mining frequent itemsets from uncertain data
摘要
Abstract
Uncertain data is widespread in some application fields such as sensor network,Web applications and so on.Uncertain data mining has become a new hotspot.Uncertain data mining includes clustering, classification, frequent itemsets mining, outlier detection, etc., in which frequent itemsets mining is one of the focus issues.This paper introduces two kinds of basic algorithms of mining frequent itemsets from traditional data: Apriori algorithm and FP-growth algorithm, and then analyses the methods proposed for mining frequent itemsets from uncertain data and uncertain data streams.A summary of research direction on uncertain data frequent itemsets mining is given.关键词
不确定数据/频繁项集/数据挖掘Key words
uncertain data/frequent itemsets/data mining分类
信息技术与安全科学引用本文复制引用
汪金苗,张龙波,邓齐志,王凤英,王勇..不确定数据频繁项集挖掘方法综述[J].计算机工程与应用,2011,47(20):121-125,5.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60873196) （the National Natural Science Foundation of China under Grant No.60873196）
山东省自然科学基金(No.ZR2010FL003) （No.ZR2010FL003）
山东理工大学博士基金. （）
