• 人工智能 •

### 一种基于文本卷积神经网络的推荐算法

1. (北方工业大学信息学院，北京100144)
• 出版日期:2020-10-14 发布日期:2020-10-14
• 作者简介:杨辉(1993—)，男，安徽合肥人，硕士研究生，研究方向：人工智能，大数据挖掘，推荐系统，E-mail: 215835380@qq.com; 王月海(1975—)，男，山东莒南人，教授，CCF容错专委委员，博士，研究方向：人工智能，大数据挖掘，智能机器人，E-mail: wangyuehai@ncut.edu.cn; 豆震泽(1995—)，男，北京人，硕士研究生，研究方向：人工智能，E-mail: 379113096@qq.com。
• 基金资助:
国家自然科学基金资助项目(61573019)

### A Recommendation Algorithm Based on Text Convolutional Neural Network

1. (School of Information, North China University of Technology, Beijing 100144, China)

• Online:2020-10-14 Published:2020-10-14

Abstract: The traditional matrix factorization model can not effectively extract the features of users and items, while the deep learning model can extract the feature information well. At present, the mainstream recommendation algorithm based on deep learning only uses the output of neural network or the product of item features and user features to make recommendation prediction, which can not fully mine the relationship between users and items. Based on this, this paper proposes a recommendation algorithm based on the combination of text convolutional neural network and bias singular value decomposition (BiasSVD). Text convolutional neural network (TextCNN) is used to fully extract the feature information of users and items, and then singular value decomposition method is used to make recommendations, which can deeply understand the document context information and further improve the accuracy of recommendation. After extensive evaluation and analysis on two real datasets of MovieLens, the recommendation accuracy of this algorithm is obviously better than that of ConvMF algorithm and mainstream deep learning recommendation algorithm.