Knowledge Commons of Institute of Automation,CAS
CSAN: Contextual Self-Attention Network for User Sequential Recommendation | |
Xiaowen Huang1,2; Shengsheng Qian1; Quan Fang1; Jitao Sang3,4; Changsheng Xu1,2 | |
2018-10 | |
会议名称 | ACM international conference on Multimedia |
会议日期 | October 22-26, 2018 |
会议地点 | Seoul, Republic of Korea |
摘要 | The sequential recommendation is an important task for online user-oriented services, such as purchasing products, watching videos, and social media consumption. Recent work usually used RNN-based methods to derive an overall embedding of the whole behavior sequence, which fails to discriminate the significance of individual user behaviors and thus decreases the recommendation performance. Besides, RNN-based encoding has fixed size and makes further recommendation application inefficient and inflexible. The online sequential behaviors of a user are generally heterogeneous, polysemous, and dynamically context-dependent. In this paper, we propose a unified Contextual Self-Attention Network (CSAN) to address the three properties. Heterogeneous user behaviors are considered in our model that are projected into a common latent semantic space. Then the output is fed into the feature-wise self-attention network to capture the polysemy of user behaviors. In addition, the forward and backward position encoding matrices are proposed to model dynamic contextual dependency. Through extensive experiments on two real-world datasets, we demonstrate the superior performance of the proposed model compared with other state-of-the-art algorithms. |
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/173211/25826 |
专题 | 多模态人工智能系统全国重点实验室_多媒体计算 |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.School of Computer and Information Technology & Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University 4.State Key Laboratory for Novel Software Technology, Nanjing University |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Xiaowen Huang,Shengsheng Qian,Quan Fang,et al. CSAN: Contextual Self-Attention Network for User Sequential Recommendation[C],2018. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
CSAN Contextual Self(3198KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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