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» Association rules mining using heavy itemsets
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107
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ADVIS
2004
Springer
15 years 3 months ago
Incremental Association Rule Mining Using Materialized Data Mining Views
Data mining is an interactive and iterative process. Users issue series of similar queries until they receive satisfying results, yet currently available data mining systems do not...
Mikolaj Morzy, Tadeusz Morzy, Zbyszko Króli...
72
Voted
ICMLA
2009
14 years 7 months ago
All-Monotony: A Generalization of the All-Confidence Antimonotony
Abstract--Many studies have shown the limits of support/confidence framework used in Apriori-like algorithms to mine association rules. One solution to cope with this limitation is...
Yannick Le Bras, Philippe Lenca, Sorin Moga, St&ea...
91
Voted
DASFAA
2007
IEEE
234views Database» more  DASFAA 2007»
15 years 4 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
74
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VLDB
2004
ACM
127views Database» more  VLDB 2004»
15 years 3 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
CINQ
2004
Springer
125views Database» more  CINQ 2004»
15 years 3 months ago
Deducing Bounds on the Support of Itemsets
Mining Frequent Itemsets is the core operation of many data mining algorithms. This operation however, is very data intensive and sometimes produces a prohibitively large output. I...
Toon Calders