- Ferenc Bodon: (Website)
A fast APRIORI implementation (FIMI03: Paper, Implementation)
Surprising Results of Trie-based FIM Algorithms (FIMI04: Paper, Implementation)
- Attila Gyenesei and Jukka Teuhola:
Probabilistic Iterative Expansion of Candidates in Mining Frequent Itemsets (FIMI03: Paper, Implementation)
- Takeaki Uno, Tatsuya Asai, Yuzo Uchida, and Hiroki Arimura: 数据挖掘工具
LCM: An Efficient Algorithm for Enumerating Frequent Closed Item Sets (FIMI03: Paper, Implementation)
LCM ver. 2: Efficient Mining Algorithms for Frequent/Closed/Maximal Itemsets (FIMI04: Paper, Implementation)
- Guimei Liu, Hongjun Lu, Jeffrey Xu Yu, Wang Wei, and Xiangye Xiao:
AFOPT: An Efficient Implementation of Pattern Growth Approach (FIMI03: Paper, Implementation)
- Doug Burdick, Manuel Calimlim, Jason Flannick, Johannes Gehrke, and Tomi Yiu: (Website)
数据挖掘研究院
MAFIA: A Performance Study of Mining Maximal Frequent Itemsets (FIMI03: Paper, Implementation)
- Gosta Grahne and Jianfei Zhu: (Website)
Efficiently Using Prefix-trees in Mining Frequent Itemsets (FIMI03: Paper, Implementation)
(FIMI04: Paper, Implementation)
- Taneli Mielikäinen: (Website)
数据挖掘交友
Intersecting data to closed sets with constraints (FIMI03: Paper, Implementation)
- Takeaki Uno and Ken Satoh:
Detailed Description of an Algorithm for Enumeration of Maximal Frequent Sets with Irredundant Dualization (FIMI03: Paper, Implementation)
- Salvatore Orlando, Claudio Lucchese, Paolo Palmerini, Raffaele Perego, and Fabrizio Silvestri: (Website)
kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets (FIMI03: Paper, Implementation)
(FIMI04: Paper, Implementation)
- Vikram Pudi and Jayant Haritsa:
ARMOR: Association Rule Mining based on ORacle (FIMI03: Paper, Implementation)
- Christian Borgelt: (Website)
Efficient Implementations of Apriori and Eclat (FIMI03: Paper, Implementation) 数据挖掘交友
(FIMI04: Paper, Implementation)
- Amos Fiat and Sagi Shporer:
AIM: Another Itemset Miner (FIMI03: Paper, Implementation)
AIM2: Improved implementation of AIM (FIMI04: Paper, Implementation)
- Walter A. Kosters and Wim Pijls: (Website) 数据挖掘实验室
Apriori, a depth-first implementation (FIMI03: Paper, Implementation)
- Osmar R. Zaïane and Mohammed El-Hajj:
COFI-tree Mining: A New Approach to Pattern Growth with Reduced Candidacy Generation (FIMI03: Paper, Implementation)
- Andrea Pietracaprina and Dario Zandolin:
Mining Frequent Itemsets using Patricia Tries (FIMI03: Paper, Implementation)
- Frédéric Flouvat, Fabien De Marchi and Jean-Marc Petit : 数据挖掘实验室
ABS: Adaptive Borders Search of frequent itemsets (FIMI04: Paper, Implementation)
- Claudio Lucchese, Salvatore Orlando and Raffaele Perego :
DCI Closed: A Fast and Memory Efficient Algorithm to Mine Frequent Closed Itemsets (FIMI04: Paper, Implementation)
- Eray Özkural and Cevdet Aykanat :
A Space Optimization for FP-Growth (FIMI04: Paper, Implementation)
- Balázs Rácz : 数据挖掘研究院
nonordfp: An FP-growth variation without rebuilding the FP-tree (FIMI04: Paper, Implementation)
- Lars Schmidt-Thieme :
Algorithmic Features of Eclat (FIMI04: Paper, Implementation)
- Yudho Giri Sucahyo and Raj P. Gopalan:
CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure (FIMI04: Paper, Implementation)
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