Mining Algorithm for Weighted FP-Growth Frequent Item Sets based on Ordered FP-Tree

Authors

  • Yuanyuan Li Master, School of Computer Science and Technology, Tianjin Polytechnic University, CHINA
  • Shaohong Yin Associate professor, School of Computer Science and Technology, Tianjin Polytechnic University, CHINA

DOI:

https://doi.org/10.31033/ijemr.9.5.22

Keywords:

Data Mining, Association Rules, Ordered FP-Tree, Weighted Model, Weighted Ordered FP-Tree

Abstract

FP-growth algorithm is a classic algorithm of mining frequent item sets, but there exist certain disadvantages for mining the weighted frequent item sets. Based on the weighted downward closure property of the weighted model, this paper proposed a method to reduce the use of storage space by constructing a weight ordered FP-tree, so as to improve the generation efficiency of weighted frequent item sets.

Downloads

Published

2019-10-31

How to Cite

Yuanyuan Li, & Shaohong Yin. (2019). Mining Algorithm for Weighted FP-Growth Frequent Item Sets based on Ordered FP-Tree. International Journal of Engineering and Management Research, 9(5), 154–158. https://doi.org/10.31033/ijemr.9.5.22