DocumentCode :
3206572
Title :
Context learning can improve user interaction
Author :
Louis, Sushil J. ; Shankar, Anil
Author_Institution :
Dept. of Comput. Sci. & Eng., Nevada Univ., Reno, NV, USA
fYear :
2004
fDate :
8-10 Nov. 2004
Firstpage :
115
Lastpage :
120
Abstract :
Current computer applications lack user context and do not learn to use this context to improve user interaction. In this paper we present Sycophant, a context learning calendar application program which learns a mapping from user-related contextual features to application actions. In this preliminary work, Sycophant achieves good accuracy in learning this mapping. In addition, we find that including external context such as the presence or absence of motion and speech provides better performance in learning accurate mappings.
Keywords :
application program interfaces; data mining; learning (artificial intelligence); sensors; user interfaces; Sycophant; application program; context learning; sensor; user context; user interaction; Application software; Calendars; Clocks; Computer applications; Computer science; Keyboards; Laboratories; Machine learning algorithms; Mice; Speech;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Reuse and Integration, 2004. IRI 2004. Proceedings of the 2004 IEEE International Conference on
Print_ISBN :
0-7803-8819-4
Type :
conf
DOI :
10.1109/IRI.2004.1431446
Filename :
1431446
Link To Document :
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