Research on Mining Multi-Weights Supports Association Rules with Frequent Pattern Growth Algorithm
碩士 === 立德管理學院 === 應用資訊研究所 === 92 === Recently years, it is important to mine item’s association rules from large database due to increasing considerable quantity of data constantly. In the past Algorithm of mining item’s association rules, most of those focus on times of trading count, but not profi...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2004
|
| Online Access: | http://ndltd.ncl.edu.tw/handle/47216864497199737395 |
| Summary: | 碩士 === 立德管理學院 === 應用資訊研究所 === 92 === Recently years, it is important to mine item’s association rules from large database due
to increasing considerable quantity of data constantly. In the past Algorithm of mining
item’s association rules, most of those focus on times of trading count, but not profit. The
main defect of that Algorithm is not effective to mining. Therefore this reason, this program has to provide a new method for improving the rate of time between mining item’s times and profit, is called MWFP-Growth (Multi- Weights Support Frequent Patterns Growth). This program alters FP-Growth to be applied to Weight Algorithm Multiple Support frequent patterns growth. It is effective to improve the defect of the rate of time of the association rules.
|
|---|