Tag Archives: topic modeling

Comparing methods to extract technical content for technological intelligence

We are developing indicators for the emergence of science and technology (S&T) topics. To do so, we extract information from various S&T information resources. This paper compares alternative ways of consolidating messy sets of key terms [e.g., using Natural Language … Continue reading

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Clustering scientific documents with topic modeling

Topic modeling is a type of statistical model for discovering the latent “topics” that occur in a collection of documents through machine learning. Currently, latent Dirichlet allocation (LDA) is a popular and common modeling approach. In this paper, we investigate … Continue reading

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