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1. 1. Neural probabilistic topic modeling of short and messy text

   University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)

   Author : Mattias Harrysson; [2016]
   Keywords : Topic modeling; Twitter; Latent Dirichlet allocation; LDA; Re-organized LDA; RO-LDA; GMM; Gaussian mixture model; Unsupervised; Machine learning;

   Abstract : Exploring massive amount of user generated data with topics posits a new way to find useful information. The topics are assumed to be “hidden” and must be “uncovered” by statistical methods such as topic modeling. However, the user generated data is typically short and messy e.g. READ MORE