Name
Abstract | ||
|---|---|---|
Mining high utility itemset is to find the itemsets that can bring higher profits to the company, which considers both of the profits and purchased quantities for the items. However, from the high utility itemsets, we cannot know what products should be recommended to the customer such that the profit can be increased when he/she bought some products. Therefore, we propose the definition of the utility association rules and proposes some approaches for mining utility association rules. According to the utility association rules, the company can clearly understand what products should be recommended to the customers when they purchased some items, such that the company can obtain greater benefits. Because there is no previous research on mining utility association rules, we only evaluate the performances of our proposed approaches for mining utility association rules. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3192975.3192987 | PROCEEDINGS OF 2018 10TH INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2018) |
Keywords | Field | DocType |
Data mining, High utility itemset, Utility association rule, Transaction database | Computer science,Operations research,Association rule learning,Database transaction,Profit (economics) | Conference |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yue-Shi Lee | 1 | 543 | 41.14 |
| Show-Jane Yen | 2 | 537 | 130.05 |