Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Weighted Association Rule Mining using weighted support and significance framework
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Algorithms for Mining Closed Itemsets and Their Lattice Structure
IEEE Transactions on Knowledge and Data Engineering
A fast high utility itemsets mining algorithm
UBDM '05 Proceedings of the 1st international workshop on Utility-based data mining
Mining itemset utilities from transaction databases
Data & Knowledge Engineering - Special issue: ER 2003
CTU-Mine: An Efficient High Utility Itemset Mining Algorithm Using the Pattern Growth Approach
CIT '07 Proceedings of the 7th IEEE International Conference on Computer and Information Technology
Isolated items discarding strategy for discovering high utility itemsets
Data & Knowledge Engineering
Weighted Association Rule Mining from Binary and Fuzzy Data
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
A Weighted Utility Framework for Mining Association Rules
EMS '08 Proceedings of the 2008 Second UKSIM European Symposium on Computer Modeling and Simulation
A Novel Algorithm for Mining High Utility Itemsets
ACIIDS '09 Proceedings of the 2009 First Asian Conference on Intelligent Information and Database Systems
Parallel Method for Mining High Utility Itemsets from Vertically Partitioned Distributed Databases
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part I
Efficiently mining high average utility itemsets with a tree structure
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part I
Discovery of high utility itemsets from on-shelf time periods of products
Expert Systems with Applications: An International Journal
An effective tree structure for mining high utility itemsets
Expert Systems with Applications: An International Journal
An efficient strategy for mining high utility itemsets
International Journal of Intelligent Information and Database Systems
HUC-Prune: an efficient candidate pruning technique to mine high utility patterns
Applied Intelligence
An incremental mining algorithm for high utility itemsets
Expert Systems with Applications: An International Journal
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In this paper, we propose a method for mining Frequent Weighted Utility Itemsets (FWUIs) from quantitative databases. Firstly, we introduce the WIT (Weighted Itemset Tidset) tree data structure for mining high utility itemsets in the work of Le et al. (2009) and modify it into MWIT (M stands for Modification) tree for mining FWUIs. Next, we propose an algorithm for mining FWUIs using MWIT-tree. We test the proposed algorithm in many databases and show that they are very efficient.