Communications of the Korean Institute of Information Scientists and Engineers (정보과학회지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
권호 표지

기계학습을 기반으로 한 사용자 주도의 시각화 분석: 문제점과 해결 방안

  • Published : 2016.11.22
Download PDF
⟨ Previous Next ⟩

Abstract

Keywords

References

  1. Cook, Kristin A., and James J. Thomas. Illuminating the path: The research and development agenda for visual analytics. No. PNNL-SA-45230. Pacific Northwest National Laboratory (PNNL), Richland, WA (US), 2005.
  2. Keim, Daniel, et al. "Visual analytics: Definition, process, and challenges." Information visualization. Springer Berlin Heidelberg, 2008. 154-175
  3. Patel, Jigar, et al. "Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques." Expert Systems with Applications 42.1 (2015): 259-268. https://doi.org/10.1016/j.eswa.2014.07.040
  4. Klimov, Denis, Alexander Shknevsky, and Yuval Shahar. "Exploration of patterns predicting renal damage in patients with diabetes type II using a visual temporal analysis laboratory." Journal of the American Medical Informatics Association 22.2 (2015): 275-289. https://doi.org/10.1136/amiajnl-2014-002927
  5. Graves, Alex, Abdel-rahman Mohamed, and Geoffrey Hinton. "Speech recognition with deep recurrent neural networks." 2013 IEEE international conference on acoustics, speech and signal processing. IEEE, 2013.
  6. Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." Advances in neural information processing systems. 2012.
  7. Keim, Daniel A., et al. "Challenges in visual data analysis." Tenth International Conference on Information Visualisation (IV'06). IEEE, 2006.
  8. Jacko, Julie A., and Andrew Sears. "The Human-Computer Interaction Handbook: Fundamentals." Evolving Technologies, and Emerging Applications: Lawrence Erlbaum and Associates (2002).
  9. Yi, Ji Soo, et al. "Toward a deeper understanding of the role of interaction in information visualization." IEEE transactions on visualization and computer graphics 13.6 (2007): 1224-1231. https://doi.org/10.1109/TVCG.2007.70515
  10. Ribeiro, Marco Tulio, Sameer Singh, and Carlos Guestrin. "" Why Should I Trust You?": Explaining the Predictions of Any Classifier." arXiv preprint arXiv: 1602.04938 (2016).
  11. Liu, Zhicheng, and Jeffrey Heer. "The effects of interactive latency on exploratory visual analysis." IEEE transactions on visualization and computer graphics 20.12 (2014): 2122-2131. https://doi.org/10.1109/TVCG.2014.2346452
  12. Zudalova, E., and T. Adriaansen. "Trends in Interactive Visualization: State-of-the-Art Survey." Advanced Information and Knowledge Processing (2009): 1-372.
  13. Kim, Hannah, et al. "InterAxis: Steering Scatterplot Axes via Observation-Level Interaction." IEEE transactions on visualization and computer graphics 22.1 (2016): 131-140. https://doi.org/10.1109/TVCG.2015.2467615
  14. Kwon, Bum Chul, et al. "AxiSketcher: Interactive Nonlinear Axis Mapping of Visualizations through User Drawings." IEEE Transactions on Visualization and Computer Graphics (2016).
  15. Brown, Eli T., et al. "Dis-function: Learning distance functions interactively." Visual Analytics Science and Technology (VAST), 2012 IEEE Conference on. IEEE, 2012.
  16. Choo, Jaegul, et al. "Utopian: User-driven topic modeling based on interactive nonnegative matrix factorization." IEEE transactions on visualization and computer graphics 19.12 (2013): 1992-2001. https://doi.org/10.1109/TVCG.2013.212
  17. Kulesza, Todd, et al. "Principles of explanatory debugging to personalize interactive machine learning." Proceedings of the 20th International Conference on Intelligent User Interfaces. ACM, 2015.
  18. Kulesza, Todd, et al. "Why-oriented end-user debugging of naive Bayes text classification." ACM Transactions on Interactive Intelligent Systems (TiiS) 1.1 (2011): 2.
  19. Van Den Elzen, Stef, and Jarke J. van Wijk. "Baobabview: Interactive construction and analysis of decision trees." Visual Analytics Science and Technology (VAST), 2011 IEEE Conference on. IEEE, 2011.
  20. Zeiler, Matthew D., and Rob Fergus. "Visualizing and understanding convolutional networks." European Conference on Computer Vision. Springer International Publishing, 2014.
  21. Yosinski, Jason, et al. "Understanding neural networks through deep visualization." arXiv preprint arXiv: 1506.06579 (2015).
  22. Xu, Kelvin, et al. "Show, attend and tell: Neural image caption generation with visual attention." arXiv preprint arXiv:1502.03044 2.3 (2015): 5.
  23. Mnih, Volodymyr, Nicolas Heess, and Alex Graves. "Recurrent models of visual attention." Advances in Neural Information Processing Systems. 2014.
  24. Agarwal, Sameer, et al. "BlinkDB: queries with bounded errors and bounded response times on very large data." Proceedings of the 8th ACM European Conference on Computer Systems. ACM, 2013.
  25. Liu, Zhicheng, Biye Jiang, and Jeffrey Heer. "imMens: Real‐time Visual Querying of Big Data." Computer Graphics Forum. Vol. 32. No. 3pt4. Blackwell Publishing Ltd, 2013.
  26. Choo, Jaegul, and Haesun Park. "Customizing computational methods for visual analytics with big data." IEEE Computer Graphics and Applications 33.4 (2013): 22-28. https://doi.org/10.1109/MCG.2013.39
  27. Kim, Minjeong, et al. "Topiclens: Efficient multi-level visual topic exploration of large-scale document collections." IEEE Transactions on Visualization and Computer Graphics.
  28. Choo, Jaegul, Changhyun Lee, and Haesun Park. "PIVE: A per-iteration visualization environment for supporting real-time interactions with computational methods." (2013).