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» Frequent regular itemset mining
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FIMI
2003
88views Data Mining» more  FIMI 2003»
13 years 9 months ago
A fast APRIORI implementation
The efficiency of frequent itemset mining algorithms is determined mainly by three factors: the way candidates are generated, the data structure that is used and the implementati...
Ferenc Bodon
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
14 years 8 months ago
An inductive database prototype based on virtual mining views
We present a prototype of an inductive database. Our system enables the user to query not only the data stored in the database but also generalizations (e.g. rules or trees) over ...
Élisa Fromont, Adriana Prado, Bart Goethals...
IS
2007
13 years 7 months ago
Discovering frequent geometric subgraphs
As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the req...
Michihiro Kuramochi, George Karypis
IPL
2006
99views more  IPL 2006»
13 years 7 months ago
Computational complexity of queries based on itemsets
We investigate determining the exact bounds of the frequencies of conjunctions based on frequent sets. Our scenario is an important special case of some general probabilistic logi...
Nikolaj Tatti
FIMI
2004
123views Data Mining» more  FIMI 2004»
13 years 9 months ago
Surprising Results of Trie-based FIM Algorithms
Trie is a popular data structure in frequent itemset mining (FIM) algorithms. It is memory-efficient, and allows fast construction and information retrieval. Many trie-related tec...
Ferenc Bodon