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Fingerprint Dive into the research topics where Hoh In is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Ubiquitous computing Engineering & Materials Science
Software engineering Engineering & Materials Science
Mobile devices Engineering & Materials Science
Wireless networks Engineering & Materials Science
Requirements engineering Engineering & Materials Science
Costs Engineering & Materials Science
Life cycle Engineering & Materials Science
Video streaming Engineering & Materials Science

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Research Output 1996 2019

  • 907 Citations
  • 15 h-Index
  • 61 Article
  • 60 Conference contribution

Automatic stop word generation for mining software artifact using topic model with pointwise mutual information

Lee, J. B., Lee, T. & In, H., 2019 Jan 1, In : IEICE Transactions on Information and Systems. E102D, 9, p. 1761-1772 12 p.

Research output: Contribution to journalArticle

Open Access
Experiments
3 Citations (Scopus)
Open Access
Circadian Rhythm
Mood Disorders
Observational Studies
Cohort Studies
Phenotype

Adaptive kinetic scrolling: Kinetic scrolling for large datasets on mobile devices

Jeong, J., Kim, N. & In, H., 2018 Oct 23, In : Applied Sciences (Switzerland). 8, 11, 2015.

Research output: Contribution to journalArticle

Mobile devices
Kinetics
kinetics
graphical user interface
Graphical user interfaces
1 Citation (Scopus)

Measuring the degree of content immersion in a nonexperimental environment using a portable EEG device

Keum, N. H., Lee, T., Lee, J. B. & In, H., 2018 Jan 1, In : Journal of Information Processing Systems. 14, 4, p. 1049-1061 13 p.

Research output: Contribution to journalArticle

Electroencephalography
Sensors
Mobile devices
Smartphones
Gages

A probabilistic approach to building defect prediction model for platform-based product lines

Jeon, C. K., Kim, N. H. & In, H., 2017, In : International Arab Journal of Information Technology. 14, 4, p. 413-422 10 p.

Research output: Contribution to journalArticle

Defects
Life cycle
Software testing
Markov processes
Managers