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» Mining Frequent Itemsets Using Support Constraints
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ICDM
2002
IEEE
167views Data Mining» more  ICDM 2002»
14 years 1 months ago
From Path Tree To Frequent Patterns: A Framework for Mining Frequent Patterns
In this paper, we propose a new framework for mining frequent patterns from large transactional databases. The core of the framework is of a novel coded prefix-path tree with two...
Yabo Xu, Jeffrey Xu Yu, Guimei Liu, Hongjun Lu
FIMI
2004
123views Data Mining» more  FIMI 2004»
13 years 10 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
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
14 years 9 months ago
Real world performance of association rule algorithms
This study compares five well-known association rule algorithms using three real-world datasets and an artificial dataset. The experimental results confirm the performance improve...
Zijian Zheng, Ron Kohavi, Llew Mason
FIMI
2003
210views Data Mining» more  FIMI 2003»
13 years 10 months ago
COFI-tree Mining: A New Approach to Pattern Growth with Reduced Candidacy Generation
Existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. Some of these major problems are: (1) the repetitive I/O disk sca...
Osmar R. Zaïane, Mohammad El-Hajj
EDBT
2008
ACM
206views Database» more  EDBT 2008»
14 years 8 months ago
Designing an inductive data stream management system: the stream mill experience
There has been much recent interest in on-line data mining. Existing mining algorithms designed for stored data are either not applicable or not effective on data streams, where r...
Hetal Thakkar, Barzan Mozafari, Carlo Zaniolo