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FIMI
2003
95views Data Mining» more  FIMI 2003»
13 years 8 months ago
Probabilistic Iterative Expansion of Candidates in Mining Frequent Itemsets
A simple new algorithm is suggested for frequent itemset mining, using item probabilities as the basis for generating candidates. The method first finds all the frequent items, an...
Attila Gyenesei, Jukka Teuhola
KDD
2000
ACM
118views Data Mining» more  KDD 2000»
13 years 10 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
ICDM
2007
IEEE
180views Data Mining» more  ICDM 2007»
14 years 27 days ago
Mining Frequent Itemsets in a Stream
We study the problem of finding frequent itemsets in a continuous stream of transactions. The current frequency of an itemset in a stream is defined as its maximal frequency ove...
Toon Calders, Nele Dexters, Bart Goethals
ICDM
2006
IEEE
140views Data Mining» more  ICDM 2006»
14 years 19 days ago
Mining the Future: Predicting Itemsets' Support of Association Rules Mining
This paper proposes a novel research dimension in the field of data mining, which is mining the future data before its arrival, or in other words: predicting association rules ahe...
Shenoda Guirguis, Khalil M. Ahmed, Nagwa M. El-Mak...
ADC
2008
Springer
156views Database» more  ADC 2008»
14 years 29 days ago
Interactive Mining of Frequent Itemsets over Arbitrary Time Intervals in a Data Stream
Mining frequent patterns in a data stream is very challenging for the high complexity of managing patterns with bounded memory against the unbounded data. While many approaches as...
Ming-Yen Lin, Sue-Chen Hsueh, Sheng-Kun Hwang