An Exploratory Study On The Appropriateness Of Latent Dirichlet Allocation For Automatic Discovery Of Product Associations From User-Generated Content
作者： Johannes Putzke , Kai Fischbach , Detlef Schoder
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摘要: Latent Dirichlet Allocation (LDA) is a method that can be used to generate word association networks from unstructured text documents. However, no study has yet examined the applicability of LDA for deriving product associations user-generated content. In this work, we apply on 9,529 and uncategorized McDonald’s reviews were crawled German online review platform. We evaluate For reason, conducted survey among 95 Information Systems undergraduate students about their with 17 McDonald’s-related nouns. Results indicate valid
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