Abstract | ||
---|---|---|
The problem of finding a suitable dataset to test different data mining algorithms and techniques and specifically association rule mining for Market Basket Analysis is a big challenge. A lot of dataset generators have been implemented in order to overcome this problem. ARtool is a tool that generates synthetic datasets and runs association rule mining for Market Basket Analysis. But the lack of datasets that include timestamps of the transactions to facilitate the analysis of Market Basket data taking into account temporal aspects is notable. In this paper, we present the TARtool. The TARtool is a data mining and generation tool based on the ARtool. TARtool is able to generate datasets with timestamps for both retail and e-commerce environments taking into account general customer buying habits in such environments. We implemented the generator to produce datasets with different format to ease the process of mining such datasets in other data mining tools. An advanced GUI is also provided. The experimental results showed that our tool overcomes other tools in efficiency, usability, functionality, and quality of generated data. |
Year | DOI | Venue |
---|---|---|
2008 | 10.1007/978-3-540-88192-6_37 | ADMA |
Keywords | Field | DocType |
data mining,market basket data,account temporal aspect,different data mining algorithm,association rule mining,generation tool,temporal dataset generator,account general customer buying,synthetic datasets,data mining tool,market basket analysis,e commerce | Data mining,Data stream mining,Market basket,Computer science,Usability,Association rule learning,Timestamp,Affinity analysis,Data mining algorithm | Conference |
Volume | ISSN | Citations |
5139 | 0302-9743 | 4 |
PageRank | References | Authors |
0.46 | 8 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Asem Omari | 1 | 4 | 2.15 |
Regina Langer | 2 | 4 | 0.46 |
Stefan Conrad | 3 | 168 | 105.91 |