Learning consumer preferences through textual and visual data: a multi-modal approach
Author:
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Publisher
Springer Science and Business Media LLC
Subject
Human-Computer Interaction,Economics, Econometrics and Finance (miscellaneous)
Link
https://link.springer.com/content/pdf/10.1007/s10660-023-09780-8.pdf
Reference76 articles.
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2. Wang, H., Zhang, F., Wang, J., Zhao, M., Li, W., Xie, X., & Guo, M. (2019). Exploring high-order user preference on the knowledge graph for recommender systems. ACM Transactions on Information Systems, 37, 1–26. https://doi.org/10.1145/3312738
3. Agichtein, E., Brill, E., & Dumais, S. (2006) Improving web search ranking by incorporating user behavior information, In Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, 19–26. https://doi.org/10.1145/1148170.1148177.
4. Liu, J., Toubia, O., & Hill, S. (2021). Content-based model of web search behavior: An application to TV show search. Management Science, 67(10), 6378–6398. https://doi.org/10.1287/mnsc.2020.3827
5. Moon, S., Jalali, N., & Erevelles, S. (2021). Segmentation of both reviewers and businesses on social media. Journal of Retailing and Consumer Services, 61, 102524. https://doi.org/10.1016/j.jretconser.2021.102524
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