Vol-126

© 2004 for the individual papers by the papers' authors. Copying permitted for private and scientific purposes. Re-publication of material on this page requires permission by the copyright owners.

FIMI '04
Workshop on Frequent Itemset Mining Implementations

Proceedings of the IEEE ICDM Workshop on
Frequent Itemset Mining Implementations
Brighton, UK, November 1, 2004

Edited by

Roberto Bayardo, IBM Almaden Research Center, USA
Bart Goethals, University of Antwerp, Belgium
Mohammed J. Zaki, Rensselaer Polytechnic Institute, USA

All datasets and sources of the implementations described in the accepted papers can be found on the FIMI repository:
http://fimi.cs.helsinki.fi/

Table of Contents

Regular Papers

Surprising Results of Trie-based FIM Algorithms
Ferenc Bodon
ABS: Adaptive Borders Search of frequent itemsets
Frédéric Flouvat, Fabien De Marchi and Jean-Marc Petit
DCI Closed: A Fast and Memory Efficient Algorithm to Mine Frequent Closed Itemsets
Claudio Lucchese, Salvatore Orlando and Raffaele Perego
A Space Optimization for FP-Growth
Eray Özkural and Cevdet Aykanat
nonordfp: An FP-growth variation without rebuilding the FP-tree
Balázs Rácz
Algorithmic Features of Eclat
Lars Schmidt-Thieme
CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure
Yudho Giri Sucahyo and Raj P. Gopalan
LCM ver. 2: Efficient Mining Algorithms for Frequent/Closed/Maximal Itemsets
Takeaki Uno, Masashi Kiyomi and Hiroki Arimura

Improved Implementations from FIMI'03

AIM2: Improved implementation of AIM
Sagi Shporer
Reducing the Main Memory Consumptions of FPmax* and FPclose
Jianfei Zhu and Gösta Grahne
kDCI: on using direct count up to the third iteration
Claudio Lucchese, Salvatore Orlando, Raffaele Perego
Recursion Pruning for the Apriori Algorithm
Christian Borgelt

Datasets

WebDocs: a real-life huge transactional dataset
Claudio Lucchese, Salvatore Orlando, Raffaele Perego and Fabrizio Silvestri

submitted by B. Goethals, June 6, 2005