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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chong Wang Yanqing Wang |
| Copyright Year | 2012 |
| Description | Author affiliation: Harbin Institute of Technology, School of Management, China (Yanqing Wang) || Business School, Huaihai Institute of Technology, Lianyungang, China (Chong Wang) |
| Abstract | In the Internet shopping environment, changes of customer's needs grow increasingly outstanding. One of the most important marketing resources is the prior daily transaction records in the consumer's database. In this study, the paper present a new methodology for predicting consumers' purchase behavior that uses consumers' purchase sequences. First, transaction clustering is conducted, then it is made that detecting the evolving consumer purchase sequences as time passes, and the consumers behaviors, which are derived from a change in the cluster number of each consumer, are kept in the purchase sequence database. Finally, sequential purchase patterns over user-specified minimum support and confidence are extracted by using the association rule. The sequential purchase patterns are then stored in the association rule database. The better result is achieved by applying the new methodogy to a given example for consumers. |
| Starting Page | 642 |
| Ending Page | 645 |
| File Size | 229480 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467300254 |
| e-ISBN | 9781467300247 |
| DOI | 10.1109/FSKD.2012.6233731 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-05-29 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Dairy products Consumer behavior Correlation Databases purchase sequence Association rules behavior change consumer Business |
| Content Type | Text |
| Resource Type | Article |
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