Personalized Cross-Domain Recommendation of Books Based on Video Consumption Data 


Vol. 13,  No. 8, pp. 382-387, Aug.  2024
https://doi.org/10.3745/TKIPS.2024.13.8.382


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  Abstract

Recently, the amount of adult reading has been continuously decreasing, but the consumption of video content is increasing. Accordingly, there is no information on preferences and behavior patterns for new users, and user evaluation or purchase of new books are insufficient, causing cold start problems and data scarcity problems. In this paper, a hybrid book recommendation system based on video content was proposed. The proposed recommendation system can not only solve the cold start problem and data scarcity problem by utilizing the contents of the video, but also has improved performance compared to the traditional book recommendation system, and even high-quality recommendation results that reflect genre, plot, and rating information-based user taste information were confirmed.

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  Cite this article

[IEEE Style]

Y. B. Lim and H. H. Kim, "Personalized Cross-Domain Recommendation of Books Based on Video Consumption Data," The Transactions of the Korea Information Processing Society, vol. 13, no. 8, pp. 382-387, 2024. DOI: https://doi.org/10.3745/TKIPS.2024.13.8.382.

[ACM Style]

Yea Bin Lim and Hyon Hee Kim. 2024. Personalized Cross-Domain Recommendation of Books Based on Video Consumption Data. The Transactions of the Korea Information Processing Society, 13, 8, (2024), 382-387. DOI: https://doi.org/10.3745/TKIPS.2024.13.8.382.