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» kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets
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ML
2010
ACM
210views Machine Learning» more  ML 2010»
13 years 7 months ago
Mining frequent closed rooted trees
Many knowledge representation mechanisms are based on tree-like structures, thus symbolizing the fact that certain pieces of information are related in one sense or another. There ...
José L. Balcázar, Albert Bifet, Anto...
RCIS
2010
13 years 7 months ago
A Tree-based Approach for Efficiently Mining Approximate Frequent Itemsets
—The strategies for mining frequent itemsets, which is the essential part of discovering association rules, have been widely studied over the last decade. In real-world datasets,...
Jia-Ling Koh, Yi-Lang Tu
ADC
2003
Springer
182views Database» more  ADC 2003»
14 years 1 months ago
CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Yudho Giri Sucahyo, Raj P. Gopalan
KDD
2002
ACM
140views Data Mining» more  KDD 2002»
14 years 9 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han
JDWM
2010
139views more  JDWM 2010»
13 years 7 months ago
Mining Frequent Generalized Patterns for Web Personalization in the Presence of Taxonomies
The Web is a continuously evolving environment, since its content is updated on a regular basis. As a result, the traditional usagebased approach to generate recommendations that ...
Panagiotis Giannikopoulos, Iraklis Varlamis, Magda...