Enhancing Topic Modeling on Short Texts with Crowdsourcing

Abstract

Topic modeling is nowadays widely used in text archive analytics, to find significant topics in news articles and important aspects of product comments available on the Internet. While statistical approaches, e.g. Latent Dirichlet Allocation (LDA) and its variants, are effective on building topic models on long texts, it remains difficult to identify… (More)

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