A Unified Framework of Latent Feature Learning in Social Media

	A Unified Framework of Latent Feature Learning in Social Media
	Yuan, Zhaoquan 1; Sang, Jitao1 ; Xu, Changsheng1 ; Liu, Yan 2
发表期刊	IEEE TRANSACTIONS ON MULTIMEDIA
	2014-10-01
卷号	16 期号:6 页码:1624-1635
文章类型	Article
摘要	The current trend in social media analysis and application is to use the pre-defined features and devoted to the later model development modules to meet the end tasks. Representation learning has been a fundamental problem in machine learning, and widely recognized as critical to the performance of end tasks. In this paper, we provide evidence that specially learned features will addresses the diverse, heterogeneous, and collective characteristics of social media data. Therefore, we propose to transfer the focus from the model development to latent feature learning, and present a unified framework of latent feature learning on social media. To address the noisy, diverse, heterogeneous, and interconnected characteristics of social media data, the popular deep learning is employed due to its excellent abstract abilities. In particular, we instantiate the proposed framework by (1) designing a novel relational generative deep learning model to solve the social media link analysis task, and (2) developing a multimodal deep learning to lambda rank model towards the social image retrieval task. We show that the derived latent features lead to improvement in both of the social media tasks.
关键词	Deep Learning Feature Learning India Buffet Process Social Media
WOS标题词	Science & Technology ; Technology
关键词[WOS]	LINK-PREDICTION ; IMAGE RETRIEVAL ; NEURAL-NETWORKS ; ALGORITHM ; RELEVANCE ; MODEL
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Telecommunications
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS记录号	WOS:000344720200011
引用统计	被引频次：21[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/2847
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.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Hong Kong Polytech Univ, Dept Comp, Kowloon 999077, Hong Kong, Peoples R China
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	Yuan, Zhaoquan,Sang, Jitao,Xu, Changsheng,et al. A Unified Framework of Latent Feature Learning in Social Media[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2014,16(6):1624-1635.
APA	Yuan, Zhaoquan,Sang, Jitao,Xu, Changsheng,&Liu, Yan.(2014).A Unified Framework of Latent Feature Learning in Social Media.IEEE TRANSACTIONS ON MULTIMEDIA,16(6),1624-1635.
MLA	Yuan, Zhaoquan,et al."A Unified Framework of Latent Feature Learning in Social Media".IEEE TRANSACTIONS ON MULTIMEDIA 16.6(2014):1624-1635.

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