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An adaptive environment for the user interface of Excel
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Split menus: effectively using selection frequency to organize menus
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Direct manipulation vs. interface agents
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Principles of mixed-initiative user interfaces
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Automatically personalizing user interfaces
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The effect of content customization on learnability and perceived workload
CHI '05 Extended Abstracts on Human Factors in Computing Systems
An empirical assessment of adaptation techniques
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Enhancing human-machine interactions: virtual interface alteration through wearable computers
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Improving menu interaction: a comparison of standard, force enhanced and jumping menus
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Improving list revisitation with ListMaps
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Faster cascading menu selections with enlarged activation areas
GI '06 Proceedings of Graphics Interface 2006
User interface façades: towards fully adaptable user interfaces
UIST '06 Proceedings of the 19th annual ACM symposium on User interface software and technology
Supporting interface customization using a mixed-initiative approach
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A field evaluation of an adaptable two-interface design for feature-rich software
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A predictive model of menu performance
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Bubbling menus: a selective mechanism for accessing hierarchical drop-down menus
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Follow the reader: filtering comments on slashdot
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Dreaming of adaptive interface agents
CHI '07 Extended Abstracts on Human Factors in Computing Systems
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Predictability and accuracy in adaptive user interfaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
AAMU: adaptive activation area menus for improving selection in cascading pull-down menus
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Genetic algorithm can optimize hierarchical menus
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Design research in digital government: a query prosthesis for voters
dg.o '08 Proceedings of the 2008 international conference on Digital government research
The effects of menu parallelism on visual search and selection
AUIC '08 Proceedings of the ninth conference on Australasian user interface - Volume 76
Optimizing hierarchical menus by genetic algorithm and simulated annealing
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Getting off the treadmill: evaluating walking user interfaces for mobile devices in public spaces
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Adaptively shortened pull down menus: location knowledge and selection efficiency
Behaviour & Information Technology
Ephemeral adaptation: the use of gradual onset to improve menu selection performance
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Performance evaluation of a genetic algorithm for optimizing hierarchical menus
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Triggering triggers and burying barriers to customizing software
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Evaluation of a personalized digital library based on cognitive styles: Adaptivity vs. adaptability
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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CHI '13 Extended Abstracts on Human Factors in Computing Systems
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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An evaluation of advanced user interface customization
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Software applications continue to grow in terms of the number of features they offer, making personalization increasingly important. Research has shown that most users prefer the control afforded by an adaptable approach to personalization rather than a system-controlled adaptive approach. No study, however, has compared the efficiency of the two approaches. In a controlled lab study with 27 subjects we compared the measured and perceived efficiency of three menu conditions: static, adaptable and adaptive. Each was implemented as a split menu, in which the top four items remained static, were adaptable by the subject, or adapted according to the subject's frequently and recently used items. The static menu was found to be significantly faster than the adaptive menu, and the adaptable menu was found to be significantly faster than the adaptive menu under certain conditions. The majority of users preferred the adaptable menu overall. Implications for interface design are discussed.