CASIA OpenIR  > 多媒体计算与图形学团队
A2CMHNE: Attention-Aware Collaborative Multimodal Heterogeneous Network Embedding
Jun Hu1; Shengsheng Qian2; Quan Fang2; Xueliang Liu1; Changsheng Xu1,2,3,4
Source PublicationACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
2019
Volume15Issue:2Pages:1-17
Abstract

Network representation learning is playing an important role in network analysis due to its effectiveness in a variety of applications. However, most existing network embedding models focus on homogeneous networks and neglect the diverse properties such as different types of network structures and associated multimedia content information. In this article, we learn node representations for multimodal heterogeneous networks, which contain multiple types of nodes and/or links as well as multimodal content such as texts and images. We propose a novel attention-aware collaborative multimodal heterogeneous network embedding method (A2CMHNE), where an attention-based collaborative representation learning approach is proposed to promote the collaboration of structure-based embedding and content-based embedding, and generate the robust node representation by introducing an attention mechanism that enables informative embedding integration. In experiments, we compare our model with existing network embedding models on two real-world datasets. Our method leads to dramatic improvements in performance by 5%, and 9% compared with five state-of-the-art embedding methods on one benchmark (M10 Dataset), and on a multi-modal heterogeneous network dataset (WeChat dataset) for node classification, respectively. Experimental results demonstrate the effectiveness of our proposed method on both node classification and link prediction tasks.

KeywordNetwork Embedding Multimodal Heterogeneous Network
Indexed BySCI
Language英语
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/25828
Collection多媒体计算与图形学团队
Affiliation1.HeFei University of Technology, Hefei, China
2.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
3.University of Chinese Academy of Sciences
4.Peng Cheng Laboratory
Recommended Citation
GB/T 7714
Jun Hu,Shengsheng Qian,Quan Fang,et al. A2CMHNE: Attention-Aware Collaborative Multimodal Heterogeneous Network Embedding[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2019,15(2):1-17.
APA Jun Hu,Shengsheng Qian,Quan Fang,Xueliang Liu,&Changsheng Xu.(2019).A2CMHNE: Attention-Aware Collaborative Multimodal Heterogeneous Network Embedding.ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,15(2),1-17.
MLA Jun Hu,et al."A2CMHNE: Attention-Aware Collaborative Multimodal Heterogeneous Network Embedding".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 15.2(2019):1-17.
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