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

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

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

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

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last updated on 2024-11-11 21:15 CET by the dblp team

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