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TCS
2008
9 years 7 months ago
Itemset frequency satisfiability: Complexity and axiomatization
Computing frequent itemsets is one of the most prominent problems in data mining. We study the following related problem, called FREQSAT, in depth: given some itemset-interval pai...
Toon Calders
KAIS
2006
164views more  KAIS 2006»
9 years 8 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis
JCIT
2008
128views more  JCIT 2008»
9 years 8 months ago
OPAM-An Efficient One Pass Association Mining Technique without Candidate Generation
This paper presents an efficient One Pass Association Mining technique i.e. OPAM, which finds all the frequent itemsets without generating any candidate sets. OPAM is basically an...
S. Roy, D. K. Bhattacharyya
CORR
2010
Springer
279views Education» more  CORR 2010»
9 years 8 months ago
Mining Frequent Itemsets Using Genetic Algorithm
In general frequent itemsets are generated from large data sets by applying association rule mining algorithms like Apriori, Partition, Pincer-Search, Incremental, Border algorithm...
Soumadip Ghosh, Sushanta Biswas, Debasree Sarkar, ...
FIMI
2003
123views Data Mining» more  FIMI 2003»
9 years 9 months ago
Apriori, A Depth First Implementation
We will discuss , the depth first implementation of APRIORI as devised in 1999 (see [8]). Given a database, this algorithm builds a trie in memory that contains all frequent item...
Walter A. Kosters, Wim Pijls
PAKDD
2010
ACM
208views Data Mining» more  PAKDD 2010»
9 years 10 months ago
Efficient Pattern Mining of Uncertain Data with Sampling
Mining frequent itemsets from transactional datasets is a well known problem with good algorithmic solutions. In the case of uncertain data, however, several new techniques have be...
Toon Calders, Calin Garboni, Bart Goethals
AMT
2006
Springer
108views Multimedia» more  AMT 2006»
9 years 10 months ago
Efficient Frequent Itemsets Mining by Sampling
As the first stage for discovering association rules, frequent itemsets mining is an important challenging task for large databases. Sampling provides an efficient way to get appro...
Yanchang Zhao, Chengqi Zhang, Shichao Zhang
KDD
2000
ACM
118views Data Mining» more  KDD 2000»
9 years 11 months ago
Generating non-redundant association rules
The traditional association rule mining framework produces many redundant rules. The extent of redundancy is a lot larger than previously suspected. We present a new framework for...
Mohammed Javeed Zaki
KDD
1999
ACM
237views Data Mining» more  KDD 1999»
10 years 6 days ago
Using Association Rules for Product Assortment Decisions: A Case Study
It has been claimed that the discovery of association rules is well-suited for applications of market basket analysis to reveal regularities in the purchase behaviour of customers...
Tom Brijs, Gilbert Swinnen, Koen Vanhoof, Geert We...
VLDB
2004
ACM
127views Database» more  VLDB 2004»
10 years 1 months ago
Computing Frequent Itemsets Inside Oracle 10G
1 Frequent itemset counting is the first step for most association rule algorithms and some classification algorithms. It is the process of counting the number of occurrences of ...
Wei Li, Ari Mozes
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