作者
Hongwei Wang, Fuzheng Zhang, Xing Xie, Minyi Guo
发表日期
2018/4/10
研讨会论文
Proceedings of the 2018 World Wide Web Conference
页码范围
1835-1844
出版商
International World Wide Web Conferences Steering Committee
简介
Online news recommender systems aim to address the information explosion of news and make personalized recommendation for users. In general, news language is highly condensed, full of knowledge entities and common sense. However, existing methods are unaware of such external knowledge and cannot fully discover latent knowledge-level connections among news. The recommended results for a user are consequently limited to simple patterns and cannot be extended reasonably. To solve the above problem, in this paper, we propose a deep knowledge-aware network (DKN) that incorporates knowledge graph representation into news recommendation. DKN is a content-based deep recommendation framework for click-through rate prediction. The key component of DKN is a multi-channel and word-entity-aligned knowledge-aware convolutional neural network (KCNN) that fuses semantic-level and …
引用总数
2018201920202021202220232024883156220259288190
学术搜索中的文章
H Wang, F Zhang, X Xie, M Guo - Proceedings of the 2018 world wide web conference, 2018