MenuOptimizer: interactive optimization of menu systems

Gilles Bailly 1 Antti Oulasvirta 2 Timo Kötzing 3 Sabrina Hoppe 2
1 LTCI - Laboratoire Traitement et Communication de l'Information
2 MPII - Max-Planck-Institut für Informatik
3 Friedrich-Schiller-Universität Jena
Abstract : Menu systems are challenging to design because design spaces are immense, and several human factors affect user behavior. This paper contributes to the design of menus with the goal of interactively assisting designers with an optimizer in the loop. To reach this goal, 1) we extend a predictive model of user performance to account for expectations as to item groupings; 2) we adapt an ant colony optimizer that has been proven efficient for this class of problems; and 3) we present MenuOptimizer, a set of interactions integrated into a real interface design tool (QtDe-signer). MenuOptimizer supports designers' abilities to cope with uncertainty and recognize good solutions. It allows designers to delegate combinatorial problems to the optimizer, which should solve them quickly enough without disrupting the design process. We show evidence that satisfactory menu designs can be produced for complex problems in minutes.
Keywords : Predictive models Interactive optimization ACM Classification Keywords H5m Information interfaces and presentation (eg HCI): Miscellaneous
Type de document :
Communication dans un congrès
ACM symposium on User interface software and technology, Oct 2013, St Andrew, United Kingdom. ACM symposium on User interface software and technology, pp.331 - 342, 2013, 〈10.1145/2501988.2502024〉
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Dernière modification le : jeudi 22 novembre 2018 - 15:05:27
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Gilles Bailly, Antti Oulasvirta, Timo Kötzing, Sabrina Hoppe. MenuOptimizer: interactive optimization of menu systems. ACM symposium on User interface software and technology, Oct 2013, St Andrew, United Kingdom. ACM symposium on User interface software and technology, pp.331 - 342, 2013, 〈10.1145/2501988.2502024〉. 〈hal-01528320〉

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