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	Multi-task Learning for Gender and Age Prediction on Chinese Microblog
	Liang Wang ; Qi Li ; Xuan Chen ; Sujian Li
	2016
关键词	multi-task learning social media neural network
英文摘要	The demographic attributes gender and age play an important role for social media applications.Previous studies on gender and age prediction mostly explore efficient features which are labor intensive.In this paper,we propose to use the multi-task convolutional neural network(MTCNN)model for predicting gender and age simultaneously on Chinese microblog.With MTCNN,we can effectively reduce the burden of feature engineering and explore common and unique representations for both tasks.Experimental results show that our method can significantly outperform the state-of-the-art baselines.; 1-11
语种	英语
出处	第五届自然语言处理与中文计算会议(NLPCC-ICCPOL2016)论文集中国计算机学会
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/480606]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Liang Wang,Qi Li,Xuan Chen,et al. Multi-task Learning for Gender and Age Prediction on Chinese Microblog. 2016-01-01.

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