Research on Book Recommendation Method Based on Review Helpfulness Filtering
赵健ZHAO Jian
(长春财经学院,长春130122 )
( Changchun University of Finance and Economics ,Changchun 130122,China )
摘要:本文在分析现有推荐算法利弊的基础上,提出了一个基于评论有用性的推荐框架。该框架引入多个深度学习算法,通过有用性评论评分样本进行训练,实验结果表明引入评论有用性信息可以提高个性化图书推荐的准确性,提高图书推荐服务的满意度.
Abstract: After the analysis of the pros and cons of existing recommendation algorithms, this study pmoposes a recommendation modelframework based on review helpfulness. The modlel introduces multiple deep learning algorithms and is trained by limited helpful reviewscoring samples. The experimental results show that introducing review helpfulness information can improve the accturacy of personalizedbook recommendation and improve the satisfaction of book recommendation service.
关键词:评论有用性;协同过滤;CNN; Bi-L.STM
Key words: review helpfulness; collaborative filtering; CNN; Bi-L.STM
价值工程-文章出处：赵健.基于评论有用性过滤的图书推荐方法研究[J].价值工程,2023,42(19):127-129.
|
