Topic categorization and representation of health community generated data
作者: Maofu LiuHe ZhangHuijun HuWei Wei
作者单位: 1Wuhan University of Science and Technology
2Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System
3Huazhong University of Science and Technology
刊名: Multimedia Tools and Applications, 2017, Vol.76 (8), pp.10541-10553
来源数据库: Springer Journal
DOI: 10.1007/s11042-015-3094-3
关键词: Health community generated dataLearning modelSemantic representationHealth topic categorization
英文摘要: The representation and categorization of professional health provider released data have been well investigated and practically implemented. These have facilitated browsing, search and high-order learning of health information. On the other hand, there has been little corresponding studies on the representation and categorization of health community generated data. It is usually more complex, inconsistent and ambiguous, and consequently raises challenges for data access and analytics. This paper explores various representations for health community generated data and categorizes these data in terms of health topics. In addition, this work utilizes pseudo-labeled data to train the supervised topic categorization models, and this makes the whole categorization process unsupervised and...
原始语种摘要: The representation and categorization of professional health provider released data have been well investigated and practically implemented. These have facilitated browsing, search and high-order learning of health information. On the other hand, there has been little corresponding studies on the representation and categorization of health community generated data. It is usually more complex, inconsistent and ambiguous, and consequently raises challenges for data access and analytics. This paper explores various representations for health community generated data and categorizes these data in terms of health topics. In addition, this work utilizes pseudo-labeled data to train the supervised topic categorization models, and this makes the whole categorization process unsupervised and...
全文获取路径: Springer  (合作)
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影响因子:1.014 (2012)

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关键词翻译
关键词翻译
  • categorization 归类
  • community 群落
  • representation 表现
  • pseudo 
  • generated 发生的
  • browsing 啃牧
  • ambiguous 含糊的
  • access 入口
  • provider 供方
  • inconsistent 不相容