Comparing end-user and intelligent remote control interface generation

Authors:
Olufisayo Omojokun;S. Pierce;L. Isbell;Prasun Dewan
Affiliations:
University of North Carolina, USA;Georgia Institute of Technology, USA;Georgia Institute of Technology, USA;University of North Carolina, USA
Venue:
Personal and Ubiquitous Computing
Year:
2006

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Abstract

Traditional remote controls typically allow users to activate functionality of a single device. Given that users activate a subset of functionality across devices to accomplish a particular task, it is attractive to consider a remote control directly supporting this behavior. We present qualitative and quantitative results from a study of two promising approaches creating such a remote control: end-user programming and machine learning. In general, results show that each approach possesses advantages and disadvantages, and that neither is optimal.