Guo Hui, Anca Ivan, et al.
ICWS 2007
Writing is a fundamental task in our daily life. Existing writing improvement tools mostly focus on low-level grammar error correction, rather than enhancing users' writing styles at the cognitive level. In this work, we present a computational approach that allows learners to have fast but effective learning experience with the help of automatic style transfer, visual stylometry analytics, machine teaching and practice. Our system provides a perfect fusion of vividly visualized style features and principles along with informative examples, which together can shape and drive personalized cognitive learning experience. We demonstrate the effectiveness of our system in a scenario of learning from William Shakespeare.
Guo Hui, Anca Ivan, et al.
ICWS 2007
Prashant Doshi, Richard Goodwin, et al.
ICWS 2004
Rama Akkiraju, Pinar Keskinocak, et al.
Applied Intelligence
Sesh Murthy, Rama Akkiraju, et al.
Interfaces