Personalized Recommendation Algorithm of Interior Design Style Based on Local Social Network


Guohui Fan, Chen Guo, Journal of Information Processing Systems Vol. 19, No. 5, pp. 576-589, Oct. 2023  

https://doi.org/10.3745/JIPS.01.0096
Keywords: Interior Design, Location-Based Social Network, Personalized Recommendation
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Abstract

To upgrade home style recommendations and user satisfaction, this paper proposes a personalized and optimized recommendation algorithm for interior design style based on local social network, which includes data acquisition by three-dimensional (3D) model, home-style feature definition, and style association mining. Through the analysis of user behaviors, the user interest model is established accordingly. Combined with the location-based social network of association rule mining algorithm, the association analysis of the 3D model dataset of interior design style is carried out, so as to get relevant home-style recommendations. The experimental results show that the proposed algorithm can complete effective analysis of 3D interior home style with the recommendation accuracy of 82% and the recommendation time of 1.1 minutes, which indicates excellent application effect.


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Cite this article
[APA Style]
Fan, G. & Guo, C. (2023). Personalized Recommendation Algorithm of Interior Design Style Based on Local Social Network. Journal of Information Processing Systems, 19(5), 576-589. DOI: 10.3745/JIPS.01.0096.

[IEEE Style]
G. Fan and C. Guo, "Personalized Recommendation Algorithm of Interior Design Style Based on Local Social Network," Journal of Information Processing Systems, vol. 19, no. 5, pp. 576-589, 2023. DOI: 10.3745/JIPS.01.0096.

[ACM Style]
Guohui Fan and Chen Guo. 2023. Personalized Recommendation Algorithm of Interior Design Style Based on Local Social Network. Journal of Information Processing Systems, 19, 5, (2023), 576-589. DOI: 10.3745/JIPS.01.0096.