UTOPIAN: User-Driven Topic Modeling Based on Interactive Nonnegative Matrix Factorization

@article{Choo2013UTOPIANUT,
  title={UTOPIAN: User-Driven Topic Modeling Based on Interactive Nonnegative Matrix Factorization},
  author={Jaegul Choo and Changhyun Lee and Chandan K. Reddy and Haesun Park},
  journal={IEEE Transactions on Visualization and Computer Graphics},
  year={2013},
  volume={19},
  pages={1992-2001}
}
Topic modeling has been widely used for analyzing text document collections. Recently, there have been significant advancements in various topic modeling techniques, particularly in the form of probabilistic graphical modeling. State-of-the-art techniques such as Latent Dirichlet Allocation (LDA) have been successfully applied in visual text analytics. However, most of the widely-used methods based on probabilistic modeling have drawbacks in terms of consistency from multiple runs and empirical… CONTINUE READING
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Customizing Computational Methods for Visual Analytics with Big Data

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