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No file available [This article belongs to Volume - 54, Issue - 1]
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-15-06-2022-214
Title : Correlation Visual Adversarial Bayesian Personalized Ranking Recommendation Model
LI Guangli, , ZHUO Jianwu, , XU Guangxin, , LI Chuanxiu, , WU Guangting, , ZHANG Hongbin,

Abstract : In order to solve three problems of traditional recommendation models, i.e., data sparsity, low robustness and the lack of deep-level semantics among heterogeneous features, a novel correlation visual adversarial Bayesian personalized ranking (CVABPR) recommendation model was proposed. First, based on the movie titles in the original MovieLens datasets, the corresponding movie posters were downloaded from Internet movie database (IMDB) to construct two multimodal datasets named MovieLens-100k-WM

Keywords : CVABPR, IMDB, Correlation Visual Adversarial Bayesian Personalized Ranking Recommendation Model In, correlation, visual