CASIA OpenIR  > 模式识别国家重点实验室  > 多媒体计算与图形学
Relational User Attribute Inference in Social Media
Fang, Quan1; Sang, Jitao1; Xu, Changsheng1; Hossain, M. Shamim2
AbstractNowadays, more and more people are engaged in social media to generate multimedia information, i.e., creating text and photo profiles and posting multimedia messages. Such multimodal social networking activities reveal multiple user attributes such as age, gender, and personal interest. Inferring user attributes is important for user profiling, retrieval, and personalization. Existing work is devoted to inferring user attributes independently and ignores the dependency relations between attributes. In this work, we investigate the problem of relational user attribute inference by exploring the relations between user attributes and extracting both lexical and visual features from online user-generated content. We systematically study six types of user attributes: gender, age, relationship, occupation, interest, and emotional orientation. In view of methodology, we propose a relational latent SVM (LSVM) model to combine a rich set of user features, attribute inference, and attribute relations in a unified framework. In the model, one attribute is selected as the target attribute and others are selected as the auxiliary attributes to assist the target attribute inference. The model infers user attributes and attribute relations simultaneously. Extensive experiments conducted on a collected dataset from Google+ with full attribute annotations demonstrate the effectiveness of the proposed approach in user attribute inference and attribute-based user retrieval.
KeywordAttribute Relation Latent Svm (lSvm) User Attribute Inference
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000356522300010
Citation statistics
Cited Times:20[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.King Saud Univ, Coll Comp & Informat Sci, SWE Dept, Riyadh 12372, Saudi Arabia
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Fang, Quan,Sang, Jitao,Xu, Changsheng,et al. Relational User Attribute Inference in Social Media[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2015,17(7):1031-1044.
APA Fang, Quan,Sang, Jitao,Xu, Changsheng,&Hossain, M. Shamim.(2015).Relational User Attribute Inference in Social Media.IEEE TRANSACTIONS ON MULTIMEDIA,17(7),1031-1044.
MLA Fang, Quan,et al."Relational User Attribute Inference in Social Media".IEEE TRANSACTIONS ON MULTIMEDIA 17.7(2015):1031-1044.
Files in This Item: Download All
File Name/Size DocType Version Access License
Relational User Attr(2825KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Fang, Quan]'s Articles
[Sang, Jitao]'s Articles
[Xu, Changsheng]'s Articles
Baidu academic
Similar articles in Baidu academic
[Fang, Quan]'s Articles
[Sang, Jitao]'s Articles
[Xu, Changsheng]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Fang, Quan]'s Articles
[Sang, Jitao]'s Articles
[Xu, Changsheng]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Relational User Attribute Inference in Social Media.pdf
Format: Adobe PDF
This file does not support browsing at this time
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.