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	Tackling sparsity, the achilles heel of social networks: Language model smoothing via social regularization
	Yan, Rui ; Li, Xiang ; Liu, Mengwen ; Hu, Xiaohua
	2015
英文摘要	Online social networks nowadays have the worldwide prosperity, as they have revolutionized the way for people to discover, to share, and to diffuse information. Social networks are powerful, yet they still have Achilles Heel: extreme data sparsity. Individual posting documents, (e.g., a microblog less than 140 characters), seem to be too sparse to make a difference under various scenarios, while in fact they are quite different. We propose to tackle this specific weakness of social networks by smoothing the posting document language model based on social regularization. We formulate an optimization framework with a social regularizer. Experimental results on the Twitter dataset validate the effectiveness and efficiency of our proposed model. ? 2015 Association for Computational Linguistics.; EI; 623-629; 2
语种	英语
出处	53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/423592]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Yan, Rui,Li, Xiang,Liu, Mengwen,et al. Tackling sparsity, the achilles heel of social networks: Language model smoothing via social regularization. 2015-01-01.

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