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Online Visual Analytics of Text Streams.

Publication ,  Journal Article
Liu, S; Yin, J; Wang, X; Cui, W; Cao, K; Pei, J
Published in: IEEE transactions on visualization and computer graphics
November 2016

We present an online visual analytics approach to helping users explore and understand hierarchical topic evolution in high-volume text streams. The key idea behind this approach is to identify representative topics in incoming documents and align them with the existing representative topics that they immediately follow (in time). To this end, we learn a set of streaming tree cuts from topic trees based on user-selected focus nodes. A dynamic Bayesian network model has been developed to derive the tree cuts in the incoming topic trees to balance the fitness of each tree cut and the smoothness between adjacent tree cuts. By connecting the corresponding topics at different times, we are able to provide an overview of the evolving hierarchical topics. A sedimentation-based visualization has been designed to enable the interactive analysis of streaming text data from global patterns to local details. We evaluated our method on real-world datasets and the results are generally favorable.

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Published In

IEEE transactions on visualization and computer graphics

DOI

EISSN

1941-0506

ISSN

1077-2626

Publication Date

November 2016

Volume

22

Issue

11

Start / End Page

2451 / 2466

Related Subject Headings

  • Software Engineering
  • 46 Information and computing sciences
  • 0802 Computation Theory and Mathematics
  • 0801 Artificial Intelligence and Image Processing
 

Citation

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Liu, S., Yin, J., Wang, X., Cui, W., Cao, K., & Pei, J. (2016). Online Visual Analytics of Text Streams. IEEE Transactions on Visualization and Computer Graphics, 22(11), 2451–2466. https://doi.org/10.1109/tvcg.2015.2509990
Liu, Shixia, Jialun Yin, Xiting Wang, Weiwei Cui, Kelei Cao, and Jian Pei. “Online Visual Analytics of Text Streams.IEEE Transactions on Visualization and Computer Graphics 22, no. 11 (November 2016): 2451–66. https://doi.org/10.1109/tvcg.2015.2509990.
Liu S, Yin J, Wang X, Cui W, Cao K, Pei J. Online Visual Analytics of Text Streams. IEEE transactions on visualization and computer graphics. 2016 Nov;22(11):2451–66.
Liu, Shixia, et al. “Online Visual Analytics of Text Streams.IEEE Transactions on Visualization and Computer Graphics, vol. 22, no. 11, Nov. 2016, pp. 2451–66. Epmc, doi:10.1109/tvcg.2015.2509990.
Liu S, Yin J, Wang X, Cui W, Cao K, Pei J. Online Visual Analytics of Text Streams. IEEE transactions on visualization and computer graphics. 2016 Nov;22(11):2451–2466.

Published In

IEEE transactions on visualization and computer graphics

DOI

EISSN

1941-0506

ISSN

1077-2626

Publication Date

November 2016

Volume

22

Issue

11

Start / End Page

2451 / 2466

Related Subject Headings

  • Software Engineering
  • 46 Information and computing sciences
  • 0802 Computation Theory and Mathematics
  • 0801 Artificial Intelligence and Image Processing