Recommender systems (RSs) provide customers with a personalized navigation experience
within the vast catalogs of products and services offered on popular online platforms …

Problems such as low recommendation precision and efficiency often exist in traditional
collaborative filtering because of the huge basic data volume. In order to solve these …

In this paper, we present a novel multimodal framework for video recommendation based on
deep learning. Unlike most common solutions, we formulate video recommendations by …

Data mining systems and methods are disclosed for associ ating users with items based on
underlying personas. The system associates each user account with one or more underlying …

Abstract n the era of digital information overload on the Internet, recommender systems act
as filtering algorithms to provide users with items that might meet their interests according to …

The Collaborative Filtering (CF) algorithms work fairly well in personalized recommendation
except in sparse data environment. To deal with the sparsity problem, researchers either …

Nowadays, the commonly used linear structure video recommendation methods have the
problems of non-personalized recommendation results and low accuracy, so it is extremely …

现今常用的线性结构视频推荐方法存在推荐结果非个性化, 精度低等问题,
故开发高精度的个性化视频推荐方法迫在眉睫. 提出了一种基于自编码器与多模态数据融合的 …