Abstract
In this paper, we propose a data mining framework that utilizes the concept of social network for the targeted advertising of products. This approach discovers the cohesive subgroups from customer's social network which is derived from customer's interaction data. Based on the set of cohesive subgroups, we infer the probabilities of customer s liking a product category from transaction records. Utilizing such information, we construct a targeted advertising system. We evaluate the proposed approach by using real email logs and library-circulation data. The experimental results show that our approach yields better quality of advertisement.
| Original language | English |
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| Title of host publication | Proceedings of the 39th Annual Hawaii International Conference on System Sciences, HICSS'06 |
| Pages | 137a |
| DOIs | |
| Publication status | Published - 2006 Oct 17 |
| Event | 39th Annual Hawaii International Conference on System Sciences, HICSS'06 - Kauai, HI, United States Duration: 2006 Jan 4 → 2006 Jan 7 |
Publication series
| Name | Proceedings of the Annual Hawaii International Conference on System Sciences |
|---|---|
| Volume | 6 |
| ISSN (Print) | 1530-1605 |
Other
| Other | 39th Annual Hawaii International Conference on System Sciences, HICSS'06 |
|---|---|
| Country | United States |
| City | Kauai, HI |
| Period | 06-01-04 → 06-01-07 |
All Science Journal Classification (ASJC) codes
- Engineering(all)
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Cite this
Yang, W. S., Cheng, H. C., Dia, J. B., & Lin, H. T. (2006). Mining social networks for targeted advertising. In Proceedings of the 39th Annual Hawaii International Conference on System Sciences, HICSS'06 (pp. 137a). [1579567] (Proceedings of the Annual Hawaii International Conference on System Sciences; Vol. 6). https://doi.org/10.1109/HICSS.2006.272