计算机与现代化Issue(11)：109-114,6.DOI:10.3969/j.issn.1006-2475.2018.11.019
基于双层注意力机制的深度学习电影推荐系统
A Deep Learning Recommendation System of Movie Based on Dual-attention Model
易黎1 1肖青秀1,2 1汤鲲32
作者信息
- 1. 南京烽火天地通信科技有限公司,江苏南京210019
- 2. 武汉邮电科学研究院,湖北武汉430074
- 折叠
摘要
Abstract
Traditional collaborative filtering technology only used the user's rating matrices on items to make recommendation. Because the rating matrices were too sparse and the traditional way did not take fully advantage of the many other features of users and objects, it led to a severe drop in recommendation accuracy for recommendation systems. In recent years, deep learning technology has made remarkable achievements in many fields of machine learning, in order to improve the traditional collaborative filtering recommendation system's situation, this paper proposed a deep learning recommendation system based on dual attention model of movie. This system used the depth learning framework to process multiple input feature information in Recommender systems, at the same time, which introduced dual attention mechanism and used the first attention layer to learn the user's preference for film characteristics and the second attention layer to learn user's preference for the complete movie in their watching list. After learning the user's preference, the experimental results show that the recommendation performance has been improved.关键词
双层注意力机制/深度学习/推荐系统/电影推荐Key words
dual attention model/ deep learning/ recommendation system/ movie recommendation分类
信息技术与安全科学引用本文复制引用
易黎1,肖青秀1,2,汤鲲3..基于双层注意力机制的深度学习电影推荐系统[J].计算机与现代化,2018,(11):109-114,6.
