Refinery: an open source topic modeling web platform
Journal of Machine Learning Research(2017)
摘要
We introduce Refinery, an open source platform for exploring large text document collections with topic models. Refinery is a standalone web application driven by a graphical interface, so it is usable by those without machine learning or programming expertise. Users can interactively organize articles by topic and also refine this organization with phrase-level analysis. Under the hood, we train Bayesian nonparametric topic models that can adapt model complexity to the provided data with scalable learning algorithms. The project website http://daeilkim.github.io/refinery/ contains Python code and further documentation.
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关键词
topic models,visualization,software
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