Jun-Feng Qu

Computational Theory and Mathematics · 2012

A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Jun-Feng Qu trusts overall

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

  1. Mohammed J. Zaki
  2. Vincent Shin-Mu Tseng
  3. Ying Liu
  4. Jiawei Han
  5. Yu-Chiang Li
  6. Chowdhury Farhan Ahmed
  7. Bai-En Shie
  8. Cheng-Wei Wu
  9. W. Liao
  10. Rakesh Agrawal

Who trusts Jun-Feng Qu overall

  1. Philippe Fournier-Viger
  2. Cheng-Wei Wu

Papers from Jun-Feng Qu's perspective

Ordered by how strongly the researchers Jun-Feng Qu trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach (Data mining and knowledge discovery)
  2. A fast high utility itemsets mining algorithm (UBDM '05)
  3. A Foundational Approach to Mining Itemset Utilities from Databases (SDM)
  4. A Two-Phase Algorithm for Fast Discovery of High Utility Itemsets (Pacific-Asia Conference on Knowledge Discovery and Data Mining)
  5. Isolated items discarding strategy for discovering high utility itemsets (Data & Knowledge Engineering)
  6. Scalable Algorithms for Association Mining
  7. Fast Algorithms for Mining Association Rules in Large Databases
  8. Efficient Tree Structures for High Utility Pattern Mining in Incremental Databases (IEEE Transactions on Knowledge and Data Engineering)
  9. Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases (IEEE Transactions on Knowledge and Data Engineering)
  10. Frequent pattern mining: current status and future directions

Their papers