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FIMI
2003
108views Data Mining» more  FIMI 2003»
13 years 6 months ago
AFOPT: An Efficient Implementation of Pattern Growth Approach
Guimei Liu, Hongjun Lu, Jeffrey Xu Yu, Wei Wang 00...
FIMI
2003
210views Data Mining» more  FIMI 2003»
13 years 6 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
FIMI
2003
84views Data Mining» more  FIMI 2003»
13 years 6 months ago
Detailed Description of an Algorithm for Enumeration of Maximal Frequent Sets with Irredundant Dualization
We describe an implementation of an algorithm for enumerating all maximal frequent sets using irredundant dualization, which is an improved version of that of Gunopulos et al. The...
Takeaki Uno, Ken Satoh
FIMI
2003
146views Data Mining» more  FIMI 2003»
13 years 6 months ago
ARMOR: Association Rule Mining based on ORacle
In this paper, we first focus our attention on the question of how much space remains for performance improvement over current association rule mining algorithms. Our strategy is...
Vikram Pudi, Jayant R. Haritsa
FIMI
2003
146views Data Mining» more  FIMI 2003»
13 years 6 months ago
Mining Frequent Itemsets using Patricia Tries
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
FIMI
2003
170views Data Mining» more  FIMI 2003»
13 years 6 months ago
kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets
This paper presents the implementation of kDCI, an enhancement of DCI [10], a scalable algorithm for discovering frequent sets in large databases. The main contribution of kDCI re...
Salvatore Orlando, Claudio Lucchese, Paolo Palmeri...
FIMI
2003
136views Data Mining» more  FIMI 2003»
13 years 6 months ago
Intersecting data to closed sets with constraints
We describe a method for computing closed sets with data-dependent constraints. Especially, we show how the method can be adapted to find frequent closed sets in a given data set...
Taneli Mielikäinen
FIMI
2003
123views Data Mining» more  FIMI 2003»
13 years 6 months ago
Apriori, A Depth First Implementation
We will discuss , the depth first implementation of APRIORI as devised in 1999 (see [8]). Given a database, this algorithm builds a trie in memory that contains all frequent item...
Walter A. Kosters, Wim Pijls
FIMI
2003
95views Data Mining» more  FIMI 2003»
13 years 6 months ago
Probabilistic Iterative Expansion of Candidates in Mining Frequent Itemsets
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
FIMI
2003
104views Data Mining» more  FIMI 2003»
13 years 6 months ago
AIM: Another Itemset Miner
We present a new algorithm for mining frequent itemsets. Past studies have proposed various algorithms and techniques for improving the efficiency of the mining task. We integrate...
Amos Fiat, Sagi Shporer