Leveraging consumer behaviors for product recommendation: an approach based on heterogeneous network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Human-Computer Interaction,Economics, Econometrics and Finance (miscellaneous)
Link
http://link.springer.com/content/pdf/10.1007/s10660-020-09441-0.pdf
Reference39 articles.
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3. Wang, Q., Yu, J., & Deng, W. (2019). An adjustable re-ranking approach for improving the individual and aggregate diversities of product recommendations. Electronic Commerce Research, 19(1), 59–79. https://doi.org/10.1007/s10660-018-09325-4.
4. Mishra, R., Kumar, P., & Bhasker, B. (2015). A web recommendation system considering sequential information. Decision Support Systems, 75, 1–10. https://doi.org/10.1016/j.dss.2015.04.004.
5. Wang, J., Huang, P., Zhao, H., Zhang, Z., Zhao, B., & Lee, D. L. (2018). Billion-scale commodity embedding for E-commerce recommendation in Alibaba. In Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 839–848). New York, NY: ACM. https://doi.org/10.1145/3219819.3219869.
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