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    FIMI
    2003
    146views Data Mining» more  FIMI 2003»
    Mining Frequent Itemsets using Patricia Tries
    13 years 6 months ago
    Mining Frequent Itemsets using Patricia Tries
    Download  sunsite.informatik.rwth-aachen.de
    We present a depth-first algorithm, PatriciaMine, that discovers all frequent itemsets in a dataset, for a given support threshold. The algorithm is main-memory based and employs...
    Andrea Pietracaprina, Dario Zandolin
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    FIMI
    2003
    120views Data Mining» more  FIMI 2003»
    MAFIA: A Performance Study of Mining Maximal Frequent Itemsets
    13 years 6 months ago
    MAFIA: A Performance Study of Mining Maximal Frequent Itemsets
    Download  www.cs.cornell.edu
    We present a performance study of the MAFIA algorithm for mining maximal frequent itemsets from a transactional database. In a thorough experimental analysis, we isolate the effec...
    Douglas Burdick, Manuel Calimlim, Jason Flannick, ...
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    FIMI
    2004
    175views Data Mining» more  FIMI 2004»
    CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure
    13 years 6 months ago
    CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure
    Download  sunsite.informatik.rwth-aachen.de
    Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
    Yudho Giri Sucahyo, Raj P. Gopalan
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    FIMI
    2003
    88views Data Mining» more  FIMI 2003»
    A fast APRIORI implementation
    13 years 6 months ago
    A fast APRIORI implementation
    Download  www.cs.bme.hu
    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
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    FIMI
    2003
    95views Data Mining» more  FIMI 2003»
    Probabilistic Iterative Expansion of Candidates in Mining Frequent Itemsets
    13 years 6 months ago
    Probabilistic Iterative Expansion of Candidates in Mining Frequent Itemsets
    Download  sunsite.informatik.rwth-aachen.de
    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
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