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» Itemset Materializing for Fast Mining of Association Rules
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SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
15 years 4 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
CAEPIA
2003
Springer
15 years 4 months ago
Text Mining Using the Hierarchical Syntactical Structure of Documents
One of the most important tasks for determining association rules consists of calculating all the maximal frequent itemsets. Specifically, some methods to obtain these itemsets hav...
Roxana Dánger, José Ruiz-Shulcloper,...
PAKDD
2010
ACM
152views Data Mining» more  PAKDD 2010»
15 years 3 months ago
Mining Association Rules in Long Sequences
Abstract. Discovering interesting patterns in long sequences, and finding confident association rules within them, is a popular area in data mining. Most existing methods define...
Boris Cule, Bart Goethals
ICEIS
2009
IEEE
15 years 5 months ago
NARFO Algorithm: Mining Non-redundant and Generalized Association Rules Based on Fuzzy Ontologies
Traditional approaches for mining generalized association rules are based only on database contents, and focus on exact matches among items. However, in many applications, the use ...
Rafael Garcia Miani, Cristiane A. Yaguinuma, Maril...
KDD
2002
ACM
128views Data Mining» more  KDD 2002»
15 years 11 months ago
Privacy preserving mining of association rules
We present a framework for mining association rules from transactions consisting of categorical items where the data has been randomized to preserve privacy of individual transact...
Alexandre V. Evfimievski, Ramakrishnan Srikant, Ra...