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Search process evaluation for a hierarchical menu system by Markov chains

机译:马尔可夫链对分层菜单系统的搜索过程评估

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摘要

When computers are used to execute tasks, it is often necessary for the user to locate a target item in a menu or a list. For example, users of word processors and spreadsheet applications select appropriate commands in a hierarchical menu to display dialog boxes and edit file or table attributes. To locate the desired information on the World Wide Web, users select the most appropriate candidate our of those presented by a search engine, and proceed through a series of hyperlinks that appear to be related to the task. This paper applies a cognitive model of the useru27s itme selection process to the task of target search in a hierarchical menu system that contains one or more of the following four operations: (1) item selection on the basis of similarity to the task, (2) consideration in various ways of the selection history when making the next selection, (3) backtracking when an appropriate item is not present among those selectable at a given point in time, and (4) abandoning the task unachieved. We model this selection process with Markov chains. We calculate the probability that task goals are achieved and the average number of selections to make until the task goals are achieved. Finally we use these results to propose a method of evaluation ghe structures of hierarchical menus and links on a website.
机译:当使用计算机执行任务时,用户通常需要在菜单或列表中找到目标项目。例如,文字处理器和电子表格应用程序的用户在分层菜单中选择适当的命令以显示对话框并编辑文件或表属性。为了在万维网上定位所需的信息,用户从搜索引擎选择的那些中选择最合适的候选者,然后继续执行一系列与任务有关的超链接。本文将用户项目选择过程的认知模型应用于包含以下四个操作中的一项或多项的分层菜单系统中的目标搜索任务:(1)基于与任务相似性的项目选择, (2)在进行下一个选择时以各种方式考虑选择历史,(3)在给定的时间点可选择的项中没有合适的项时进行回溯,以及(4)放弃未完成的任务。我们使用马尔可夫链对该选择过程进行建模。我们计算出达到任务目标的可能性,以及直到达到任务目标为止的平均选择次数。最后,我们使用这些结果提出一种评估网站上的分层菜单和链接的结构的方法。

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