Knowledge Commons of Institute of Automation,CAS
Multi-level News Recommendation via Modeling Candidate Interactions | |
Sun, Ying1,2![]() ![]() ![]() | |
2022-03 | |
会议名称 | 2022 7th International Conference on Big Data Analytics (ICBDA) |
会议日期 | Mar. 4-6, 2022 |
会议地点 | Online Conference |
摘要 | Due to the information explosion on the Internet, news recommendation, which helps users quickly find the news they are interested in, has become an essential issue for online news services. Previous research work usually adopts collaborative filtering or content-based methods which extract features and measure the similarities between users and each candidate news independently. However, candidate news often competes with each other for user attention, and modeling the interactions of multiple candidate news helps distinguish them better for news recommendation. In this paper, we propose a multi-level news recommendation method via modeling the interactions of multiple candidate news explicitly. Specifically, we design a Candidate Interaction Module (CIM) to generate interaction-enhanced candidate news representations. For each candidate news, the interaction-enhanced news representation contains information from other candidate news displayed to the user at the same time. Furthermore, in order to identify the connections between candidate news and user preferences at different semantic levels, we add a Multi-level Prediction Module (MPM) to exploit the category and subcategory information of news. Experimental results demonstrate that our proposed model achieves the state-of-the-art performance on two real-world benchmark datasets. |
关键词 | news recommendation candidate news interaction multi-level prediction user modeling |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48793 |
专题 | 多模态人工智能系统全国重点实验室_互联网大数据与信息安全 |
通讯作者 | Kong, Qingchao |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences 3.College of Engineering, Peking University |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Sun, Ying,Kong, Qingchao,Mao, Wenji,et al. Multi-level News Recommendation via Modeling Candidate Interactions[C],2022. |
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BAI22-249.pdf(502KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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