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To tackle these problems, we enrich the latent representations by incorporating user-generated content and item raw content. ... In addition, we further explore the relative importance of various item metadata information on improving the rating prediction performance towards personalized product recommendation, which is extremely ... rating prediction task in product recommendation. e method is capable of incorporating user-generated content and item raw content including numerical ratings, textual reviews, and item metadata in a ...doi:10.1155/2020/4780191 fatcat:r5pixfcteze3hi46bdouxjnlp4
A recommender system is a framework that is a filtering system that filters the data with various algorithms and recommends the user with the most relevant data. ... Recommendation systems are productive customization mechanisms, often up-to-date and recommendations based on current consumer preferences. ... Cold start problem and Sparsity problem can arise if there is no web browsing history. 2 DeepFusion: Fusing User-Generated Content and Item Raw Content towards Personalized Product Recommendation ...doi:10.22214/ijraset.2021.37024 fatcat:2ans7okg5jbpri7lxpr633kqam