基于TextCNN模型的电子期刊文献推荐方法研究
Research on the Method of Electronic Literature Recommendation Based on TextCNN Model
刁羽 1薛红1
作者信息
- 1. 四川轻化工大学图书馆 四川自贡,643000
- 折叠
摘要
论文提出基于TextCNN模型的电子期刊文献推荐方法,旨在更好地精确把握文献内容的本质特征与用户文献需求的深层关系,实现电子期刊文献推荐服务的个性化和精准化.使用word2vec对文献题录信息进行向量化,使用TextCNN模型训练文献推荐模型,最后主动将符合用户需求的文献推送给科研用户.实践证明,论文设计的推荐模型能够为用户推荐电子期刊文献,效果良好.
Abstract
This paper puts forward the method of electronic journal literature recommendation based on TextCNN model,aiming to better accurately grasp the deep relationship between the essential characteristics of literature content and the demands of users,and realize the personalization and precision of electronic journal literature recommendation service.The word2vec is used to vector quantify the literature title information,the TextCNN model is used to train the literature recommendation model,and finally the literature that meets user needs is actively pushed to scientific research users.Practice has proved that the recommendation model designed in this paper can recommend electronic journal literature for users with good results.
关键词
TextCNN/文本分类/电子期刊文献推荐/行为数据Key words
TextCNN/Text classification/Electronic literature recommendation/Behavior data引用本文复制引用
出版年
2024
NETL
NSTL
万方数据