论文标题

菜单系统的基于觅食的优化

Foraging-based Optimization of Menu Systems

论文作者

Dayama, Niraj Ramesh, Shiripour, Morteza, Oulasvirta, Antti, Ivanko, Evgeny, Karrenbauer, Andreas

论文摘要

菜单系统的计算设计已在有限的情况下(例如线性菜单(列表))作为分配任务解决,其中命令被分配给菜单位置,同时为用户选择性能和相关项目的距离进行优化。我们表明,这种方法在较大的,分层组织的菜单系统中跌落,还必须考虑用户如何浏览层次结构。本文提出了一种新颖的整数编程公式,该公式将层次菜单模拟为确切集合问题和分配问题的结合。它通过信息觅食理论将命令通过新的目标函数组织为有序组的有序组。一方面,它最大程度地减少了选择一个命令所需的时间,该命令的位置是从以前的用法中知道的,另一方面是在菜单中无关的部分中浪费的时间,同时搜索尚不清楚的位置的命令。这两个因素的收敛性产生了单个模型可用的,有序的命令层次结构。在生成的菜单中,组或选项卡的铅(第一个)元素是其余内容的良好指标,从而促进了搜索过程。在受控的可用性评估中,相对于选择时间,计算设计的菜单的性能比现有商业设计快25。该算法对于该问题的大型代表性实例有效。我们进一步显示了菜单系统个性化和适应性的应用。

Computational design of menu systems has been solved in limited cases such as the linear menu (list) as an assignment task, where commands are assigned to menu positions while optimizing for for users selection performance and distance of associated items. We show that this approach falls short with larger, hierarchically organized menu systems, where one must also take into account how users navigate hierarchical structures. This paper presents a novel integer programming formulation that models hierarchical menus as a combination of the exact set covering problem and the assignment problem. It organizes commands into ordered groups of ordered groups via a novel objective function based on information foraging theory. It minimizes, on the one hand, the time required to select a command whose location is known from previous usage and, on the other, the time wasted in irrelevant parts of the menu while searching for commands whose location is not known. The convergence of these two factors yields usable, well-ordered command hierarchies from a single model. In generated menus, the lead (first) elements of a group or tab are good indicators of the remaining contents, thereby facilitating the search process. In a controlled usability evaluation, the performance of computationally designed menus was 25 faster than existing commercial designs with respect to selection time. The algorithm is efficient for large, representative instances of the problem. We further show applications in personalization and adaptation of menu systems.

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