Abstract
Some portal sites have been providing price-comparison services. For the price-comparison services, however, they do not provide personalized recommendations. This paper proposes a strategy of recommendations for the price-comparison services. The strategy uses the click-log data to identify user's preference. We apply the strategy to three recommendation methods. Through the experiments, we have shown the possibility of recommendation for price-comparison services with the real-world data.
| Original language | English |
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| Title of host publication | Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013 |
| Pages | 116-117 |
| Number of pages | 2 |
| DOIs | |
| Publication status | Published - 2013 |
| Event | 2013 Research in Adaptive and Convergent Systems, RACS 2013 - Montreal, QC, Canada Duration: 2013 Oct 1 → 2013 Oct 4 |
Publication series
| Name | Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013 |
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Other
| Other | 2013 Research in Adaptive and Convergent Systems, RACS 2013 |
|---|---|
| Country | Canada |
| City | Montreal, QC |
| Period | 13/10/1 → 13/10/4 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
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Cite this
Lee, S. C., Kim, S. W., & Park, S. (2013). Recommendation in online shopping malls: Results and experiences. In Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013 (pp. 116-117). (Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013). https://doi.org/10.1145/2513228.2513254