计算机与现代化Issue(2)：100-107,8.DOI:10.3969/j.issn.1006-2475.2024.02.016
基于多视图的知识感知推荐系统
Multi-view Knowledge-aware Recommender System
摘要
Abstract
At present,most of the recommendation methods based on knowledge graph use single user or item representation,which has the problems of user interest interference,incomplete use of information and sparse data.This paper proposes a multi-view knowledge-aware recommendation model(MVKA).Firstly,the model captures the user's interest representation in the user-item graph fusion attention mechanism.Introduce the project-entity diagram,the graph attention network is used for feature extraction to obtain the embedded representation of the item.Then,a comparative learning method of graph perspective is con-structed between the two views.Finally,summation and concatenation operations are carried out to get the final representation of the user and the project,and the matching score of the user to the project is predicted by the inner product.In order to verify the accuracy and computational efficiency of the experiment,a large number of experiments were carried out on the three public data-sets of MovieLens-1M,Book-crossing and Last FM,and compared with other traditional methods and graph neural network mod-els,the AUC and F1 value evaluation indicators were significantly improved,indicating that the MVKA model can significantly use various information relationship data to improve the knowledge perception recommendation task.关键词
知识感知推荐系统/注意力机制/图注意力网络/对比学习Key words
knowledge perception recommendation system/attention mechanism/graph attention network/contrastive learning分类
信息技术与安全科学引用本文复制引用
王晓霞,孟佳娜,江烽,丁梓晴..基于多视图的知识感知推荐系统[J].计算机与现代化,2024,(2):100-107,8.基金项目
国家自然科学基金资助项目(61876031) （61876031）
辽宁省自然科学基金一般项目(2022-BS-104) （2022-BS-104）
