A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
Towards Non-linear Social Recommendation Using Gaussian Process
2022
IEEE Access
Recent research on recommender systems has proved that by leveraging social network information, the quality of recommendations can be evidently improved. Traditional social recommendation models typically linearly combine social network information. For instance, matrix factorization based models linearly combine latent factors of relevant users and items. However, in practice, the multifaceted social relations are so complex that simple linear combination may not be able to reasonably
doi:10.1109/access.2022.3141795
fatcat:v22i5psz35gezfl2u3fyfdge7q