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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hsiangchu Lai Tzyy-Ching Yang |
| Copyright Year | 2000 |
| Description | Author affiliation: Dept. of Inf. Manage., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan (Hsiangchu Lai; Tzyy-Ching Yang) |
| Abstract | Because of the intelligent computing specialty of the World Wide Web, extensive customized marketing can be executed at much lower cost and has become an emerging research issue. Therefore, the first purpose of this paper is to propose a system framework to serve as a foundation for developing a customized marketing system on the Web according to the discussions on data sources, data categories, and inference foundations. Most previous studies used induction-learning techniques to perform individual-based inference for customized marketing. However, it not only costs more to learn the personal preferences, but also some difficulties occur from using induction-learning techniques. The second purpose of this paper is to solve these problems. A group-based approach that integrates clustering and association rules is proposed. We conducted a field study to collect data to demonstrate the proposed group-based inference approach and evaluate its performance. The results reveal that this integrated approach can learn both more detailed and precise rules. |
| File Size | 1504171 |
| File Format | |
| ISBN | 0769504930 |
| DOI | 10.1109/HICSS.2000.926875 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2000-01-07 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Costs Association rules Marketing management Sun Web sites Customer satisfaction Marketing and sales Demography Web server Inference mechanisms |
| Content Type | Text |
| Resource Type | Article |
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