Masashi Kiyomi

Workshop on Frequent Itemset Mining Implementations · 2004

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Masashi Kiyomi trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Gösta Grahne
  2. Jiawei Han
  3. Douglas Burdick
  4. Rakesh Agrawal
  5. Jian Pei

Who trusts Masashi Kiyomi overall

  1. Siegfried Nijssen

Papers from Masashi Kiyomi's perspective

Ordered by how strongly the researchers Masashi Kiyomi trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Efficiently mining long patterns from databases
  2. MAFIA: a maximal frequent itemset algorithm for transactional databases (Proceedings / International Conference on Data Engineering)
  3. Fast Discovery of Association Rules
  4. Mining frequent patterns without candidate generation
  5. Efficiently Using Prefix-trees in Mining Frequent Itemsets (Workshop on Frequent Itemset Mining Implementations)
  6. Fast Algorithms for Mining Association Rules in Large Databases
  7. Mining association rules between sets of items in large databases
  8. CLOSET: An Efficient Algorithm for Mining Frequent Closed Itemsets (ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery)
  9. A Tree Projection Algorithm for Generation of Frequent Item Sets (J. Parallel Distributed Comput.)
  10. Scalable Algorithms for Association Mining

Their papers