Deep Contrastive Multiview Network Embedding | |
Mengqi Zhang1,2; Yanqiao Zhu1,2; Qiang Liu1,2; Shu Wu1,2; Liang Wang1,2 | |
2022-10-17 | |
会议日期 | 2022-10-17 |
会议地点 | New York, NY, USA |
英文摘要 | Multiview network embedding aims at projecting nodes in the network to low-dimensional vectors, while preserving their multiple relations and attribute information. Contrastive learning approaches have shown promising performance in this task. However, they neglect the semantic consistency between fused and view representations and have difficulty in modeling complementary information between different views. To deal with these deficiencies, this work presents a novel Contrastive leaRning framEwork for Multiview network Embedding (CREME). In our work, different views can be obtained based on the various relations among nodes. Then, we generate view embeddings via proper view encoders and utilize an attentive multiview aggregator to fuse these representations. Particularly, we design two collaborative contrastive objectives, view fusion InfoMax and inter-view InfoMin, to train the model in a self-supervised manner. The former objective distills information from embeddings generated from different views, while the latter captures complementary information among views to promote distinctive view embeddings. We also show that the two objectives can be unified into one objective for model training. Extensive experiments on three real-world datasets demonstrate that our proposed CREME is able to consistently outperform state-of-the-art methods. |
会议录 | Proceedings of the 31st ACM International Conference on Information and Knowledge Management |
语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/52307] |
专题 | 自动化研究所_智能感知与计算研究中心 |
通讯作者 | Shu Wu |
作者单位 | 1.Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Mengqi Zhang,Yanqiao Zhu,Qiang Liu,et al. Deep Contrastive Multiview Network Embedding[C]. 见:. New York, NY, USA. 2022-10-17. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论