| 基于深度学习的个性化新闻推荐 |
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| 引用本文： | 吴方照,武楚涵,安鸣霄,谢幸.基于深度学习的个性化新闻推荐[J].南京气象学院学报,2019,11(3):278-285. |
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| 作者姓名： | 吴方照 武楚涵 安鸣霄 谢幸 |
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| 作者单位： | 微软亚洲研究院, 北京, 100080,清华大学 信息科学技术学院, 北京, 100084,中国科学技术大学 计算机科学与技术学院, 合肥, 230026,微软亚洲研究院, 北京, 100080 |
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| 摘 要： | 由于网络上每天有海量的新闻报道产生，新闻推荐已经成为减轻用户信息负载、实现个性化新闻信息获取的重要途径，并被广泛用于新闻网站和新闻APP中以提升用户体验.不同于传统的商品推荐，在新闻推荐中新的新闻文章产生速度很快，而且新闻的语义信息需要结合整体新闻文本去理解，给传统的基于ID和基于特征的推荐算法带来了很大的挑战.此外，用户的新闻阅读兴趣存在高度多样性和动态性的特点，使得准确的用户建模变得非常困难.本文介绍了一些基于深度学习的个性化新闻推荐算法，并探讨了新闻推荐未来的一些可行的方向.
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| 关 键 词： | 推荐系统 新闻推荐 用户建模 深度神经网络 |
| 收稿时间： | 2019/5/16 0:00:00 |
Personalized news recommendation based on deep learning |
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| WU Fangzhao,WU Chuhan,AN Mingxiao and XIE Xing.Personalized news recommendation based on deep learning[J].Journal of Nanjing Institute of Meteorology,2019,11(3):278-285. |
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| Authors: | WU Fangzhao WU Chuhan AN Mingxiao and XIE Xing |
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| Institution: | Microsoft Research Asia, Beijing 100080,School of Information Science and Technology, Tsinghua University, Beijing 100084,School of Computer Science and Technology, University of Science and Technology of China, Hefei 230026 and Microsoft Research Asia, Beijing 100080 |
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| Abstract: | Since massive news articles are generated and posted online,news recommendation has become an important way to alleviate user information overload and achieve personalized news information access,which has been widely used in many news websites and news APPs to improve user experience.Different from the traditional product recommendation,in the scenario of news recommendation,the news articles are generated very quickly,and the semantic meaning of news articles needs to be captured from the original news textual content,which bring huge challenges to the traditional recommendation methods which are based on IDs and features.In addition,users'' news reading interests are highly diverse and dynamic,making it difficult to accurately model users.In this paper we will introduce several deep learning based news recommendation algorithms,and explore several future directions of news recommendation. |
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| Keywords: | recommender system news recommendation user modeling deep neural network |
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