CASIA OpenIR
A(2) CMHNE: Attention-Aware Collaborative Multimodal Heterogeneous Network Embedding
Hu, Jun1; Qian, Shengsheng2; Fang, Quan2; Liu, Xueliang1; Xu, Changsheng3,4,5
Source PublicationACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
ISSN1551-6857
2019-06-01
Volume15Issue:2Pages:17
Corresponding AuthorHu, Jun(hujunxianligong@gmail.com)
AbstractNetwork 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 (A(2)CMHNE), 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
DOI10.1145/3321506
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61432019] ; National Natural Science Foundation of China[61702509] ; National Natural Science Foundation of China[61802405] ; National Natural Science Foundation of China[61720106006] ; National Natural Science Foundation of China[61572503] ; National Natural Science Foundation of China[61772170] ; National Natural Science Foundation of China[61632007] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-JSC039] ; K. C. Wong Education Foundation
Funding OrganizationNational Natural Science Foundation of China ; Key Research Program of Frontier Sciences, CAS ; K. C. Wong Education Foundation
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods
WOS IDWOS:000477935400016
PublisherASSOC COMPUTING MACHINERY
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/27816
Collection中国科学院自动化研究所
Corresponding AuthorHu, Jun
Affiliation1.HeFei Univ Technol, 193 Tunxi Rd, Hefei 230009, Anhui, Peoples R China
2.Chinese Acad Sci, Inst Automat, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, HeFei Univ Technol, Chinese Acad Sci, Inst Automat, Shenzhen, Peoples R China
4.Peng Cheng Lab, Shenzhen, Peoples R China
5.95 Zhongguancun East Rd, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Hu, Jun,Qian, Shengsheng,Fang, Quan,et al. A(2) CMHNE: Attention-Aware Collaborative Multimodal Heterogeneous Network Embedding[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2019,15(2):17.
APA Hu, Jun,Qian, Shengsheng,Fang, Quan,Liu, Xueliang,&Xu, Changsheng.(2019).A(2) CMHNE: Attention-Aware Collaborative Multimodal Heterogeneous Network Embedding.ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,15(2),17.
MLA Hu, Jun,et al."A(2) CMHNE: Attention-Aware Collaborative Multimodal Heterogeneous Network Embedding".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 15.2(2019):17.
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