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Comparing end-user and intelligent remote control interface generation

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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.

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Acknowledgements

This research was funded in part by Microsoft and NSF grants ANI 0229998, EIA 03-03590 and IIS 0312328.

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Authors and Affiliations

  1. University of North Carolina, CB3175, Sitterson Hall, Chapel Hill, NC, USA

    Olufisayo Omojokun & Prasun Dewan

  2. Georgia Institute of Technology, 801 Atlantic Avenue, Atlanta, GA, USA

    Jeffrey S. Pierce & Charles L. Isbell

Authors
  1. Olufisayo Omojokun
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  2. Jeffrey S. Pierce
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  3. Charles L. Isbell
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  4. Prasun Dewan
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Correspondence to Olufisayo Omojokun.

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Omojokun, O., Pierce, J.S., Isbell, C.L. et al. Comparing end-user and intelligent remote control interface generation. Pers Ubiquit Comput 10, 136–143 (2006). https://doi.org/10.1007/s00779-005-0019-6

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  • DOI: https://doi.org/10.1007/s00779-005-0019-6

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