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» Mining Frequent Itemsets Using Support Constraints
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ICDM
2002
IEEE
167views Data Mining» more  ICDM 2002»
15 years 4 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»
15 years 1 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»
16 years 5 days 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»
15 years 1 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»
15 years 12 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