Name
Abstract | ||
|---|---|---|
Discount is important in buying behavior and purchasing habits. In this paper, we focus on buying behavior which discount strategy can encourage shopping to devise strategies to boost business owners' sales. This paper introduces a new problem for mining from discounted transaction, and proposes a mining method called the DTM algorithm, which is based on sliding window for maintaining stream transactions. Through the use of this approach, the specific time points at which frequent patterns have a significant increase or decrease in frequency are effectively captured. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/SC2.2017.28 | 2017 IEEE 7th International Symposium on Cloud and Service Computing (SC2) |
Keywords | Field | DocType |
Transaction mining,Discounted transaction pattern,Memory constant,Spark | Microsoft Windows,Sliding window protocol,Computer science,Purchasing,Database transaction,Database | Conference |
ISBN | Citations | PageRank |
978-1-5386-5863-5 | 0 | 0.34 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei-Yuan Lee | 1 | 0 | 0.34 |
| Chih-Hua Tai | 2 | 2 | 2.08 |
| Yue-Shan Chang | 3 | 295 | 37.68 |