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» Statistical Supports for Frequent Itemsets on Data Streams
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ISCI
2007
99views more  ISCI 2007»
14 years 11 months ago
Privacy-preserving algorithms for distributed mining of frequent itemsets
Standard algorithms for association rule mining are based on identification of frequent itemsets. In this paper, we study how to maintain privacy in distributed mining of frequen...
Sheng Zhong
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
16 years 1 days ago
Dense itemsets
Frequent itemset mining has been the subject of a lot of work in data mining research ever since association rules were introduced. In this paper we address a problem with frequen...
Heikki Mannila, Jouni K. Seppänen
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
16 years 1 days ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
IDA
2008
Springer
14 years 11 months ago
Mining frequent items in a stream using flexible windows
We study the problem of finding frequent items in a continuous stream of itemsets. A new frequency measure is introduced, based on a flexible window length. For a given item, its ...
Toon Calders, Nele Dexters, Bart Goethals
DASFAA
2007
IEEE
234views Database» more  DASFAA 2007»
15 years 6 months ago
Estimating Missing Data in Data Streams
Networks of thousands of sensors present a feasible and economic solution to some of our most challenging problems, such as real-time traffic modeling, military sensing and trackin...
Nan Jiang, Le Gruenwald