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This paper presents an approach to help designers create their own application-specific gestures and evaluate them in user-studies based on low fidelity prototypes of the application they are designing. In order to learn custom gestures, we developed a machine learning tool that uses an anti-unification algorithm to learn based on samples of the gesture provided by the designer.
Generated: 16/10/2012