机译:具有单词向量和实体向量的神经主题模型,短文本
School of Computer Science Beihang University Beijing 100191 China;
School of Computer Science Beihang University Beijing 100191 China;
School of Computer Science Beihang University Beijing 100191 China;
National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing 100029 China;
School of Computer Science Beihang University Beijing 100191 China;
Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing 100190 China Xiamen Data Intelligence Academy of ICT CAS China;
Topic model; Short text; Variational auto-encoder; Word embedding; Entity embedding;
机译:通过学习单词和隐藏主题的向量表示来改善短文本分类
机译:基于LDA三路决策混合主题矢量模型的短文本情感分析
机译:基于LDA三路决策混合主题矢量模型的短文本情感分析
机译:导航侦查主题趋势的词的传染媒介表示在短篇文本
机译:事物和字符串和更多:通过组合实体共同发生,主题建模和单词嵌入来改善从短文本的歧义
机译:WET:MOOC视频讲座数据集的词嵌入主题分布向量
机译:导航侦查主题趋势的词的传染媒介表示在短篇文本