TopicLens: Efficient Multi-Level Visual Topic Exploration of Large-Scale Document Collections

Minjeong Kim, Kyeongpil Kang, Deokgun Park, Jaegul Choo, Niklas Elmqvist

Research output: Contribution to journalArticlepeer-review

66 Citations (Scopus)


Topic modeling, which reveals underlying topics of a document corpus, has been actively adopted in visual analytics for large-scale document collections. However, due to its significant processing time and non-interactive nature, topic modeling has so far not been tightly integrated into a visual analytics workflow. Instead, most such systems are limited to utilizing a fixed, initial set of topics. Motivated by this gap in the literature, we propose a novel interaction technique called TopicLens that allows a user to dynamically explore data through a lens interface where topic modeling and the corresponding 2D embedding are efficiently computed on the fly. To support this interaction in real time while maintaining view consistency, we propose a novel efficient topic modeling method and a semi-supervised 2D embedding algorithm. Our work is based on improving state-of-the-art methods such as nonnegative matrix factorization and t-distributed stochastic neighbor embedding. Furthermore, we have built a web-based visual analytics system integrated with TopicLens. We use this system to measure the performance and the visualization quality of our proposed methods. We provide several scenarios showcasing the capability of TopicLens using real-world datasets.

Original languageEnglish
Article number7539597
Pages (from-to)151-160
Number of pages10
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number1
Publication statusPublished - 2017 Jan

Bibliographical note

Publisher Copyright:
© 2016 IEEE.


  • magic lens
  • nonnegative matrix factorization
  • t-distributed stochastic neighbor embedding
  • text analytics
  • topic modeling

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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