FUFM-High Utility Itemsets in Transactional Database
Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.3, No. 3)Publication Date: 2014-03-30
Authors : S.Priya E.Thenmozhi D.Shiny Irene;
Page : 889-893
Keywords : Candidate pruning; frequent itemset; high utility itemset; utility mining; data mining;
Abstract
The practical usefulness of the frequent item set mining is limited by the significance of the discovered itemsets. There are two principal limitations. A huge number of frequent item sets that are not interesting to the user are often generate when the minimum support is low.Proposing two algorithms, namely utility pattern growth (UP-Growth) and UP-Growth+, for mining high utility itemsets with a set of effective strategies for pruning candidate itemsets.
Other Latest Articles
- Identity Management System to Ensure Cloud Security?
- LOW POWER QVCO USING ADIABATIC LOGIC?
- Analysis of Integer Transformation and Quantization Blocks using H.264 Standard and the Conventional DCT Techniques?
- Secured Energy Optimization for Wireless Multimedia Sensor Networks using Fuzzy logic?
- IMPLEMENTING JOINT IDLE QUEUE ALGORITHM IN CLOUD ENVIRONMENT?
Last modified: 2014-03-29 21:07:08