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A simple documentary topic analysis implement based on traditional K-means and LDA which can achieve a not-bad result. 基于Kmeans与Lda模型的多文档主题聚类,输入多篇文档,输出每个主题的关键词与相应文本,可用于主题发现与热点分析等应用,如历时话题建模,评论画像等。

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TopiCluster

基于Kmeans与Lda模型的多文档主题聚类,输入多篇文档,输出每个主题的关键词与相应文本,可用于主题发现与热点分析
If any question about the project or me ,see https://liuhuanyong.github.io/

如有自然语言处理、知识图谱、事理图谱、社会计算、语言资源建设等问题或合作,可联系我:
1、我的github项目介绍:https://liuhuanyong.github.io
2、我的csdn博客:https://blog.csdn.net/lhy2014
3、about me:刘焕勇,中国科学院软件研究所,[email protected]

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A simple documentary topic analysis implement based on traditional K-means and LDA which can achieve a not-bad result. 基于Kmeans与Lda模型的多文档主题聚类,输入多篇文档,输出每个主题的关键词与相应文本,可用于主题发现与热点分析等应用,如历时话题建模,评论画像等。

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