SAC
2006
ACM
14 years 5 months ago
2006
ACM
This paper explores the generation of candidates, which is an important step in frequent itemset mining algorithms, from a theoretical point of view. Important notions in our prob...
PKDD
2007
Springer
14 years 5 months ago
2007
Springer
Frequent itemset mining assists the data mining practitioner in searching for strongly associated items (and transactions) in large transaction databases. Since the number of frequ...
AUSDM
2007
Springer
14 years 5 months ago
2007
Springer
Mining High Utility Itemsets from a transaction database is to find itemsests that have utility above a user-specified threshold. This problem is an extension of Frequent Itemset ...
PODS
2004
ACM
14 years 11 months ago
2004
ACM
Computing frequent itemsets is one of the most prominent problems in data mining. We introduce a new, related problem, called FREQSAT: given some itemset-interval pairs, does ther...
KDD
2004
ACM
14 years 12 months ago
2004
ACM
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...
KDD
2006
ACM
14 years 12 months ago
2006
ACM
In this work we focus on the problem of frequent itemset mining on large, out-of-core data sets. After presenting a characterization of existing out-of-core frequent itemset minin...
KDD
2009
ACM
14 years 12 months ago
2009
ACM
Probabilistic frequent itemset mining in uncertain transaction databases semantically and computationally differs from traditional techniques applied to standard "certain&quo...
ICDT
2009
ACM
15 years 4 days ago
2009
ACM
In this paper, we present a comprehensive theoretical analysis of the sampling technique for the association rule mining problem. Most of the previous works have concentrated only...
ICDE
2008
IEEE
15 years 24 days ago
2008
IEEE
Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...