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Adaptive Recognition of Implicit Structures in Human-Organized Layouts

机译:人为布局中隐式结构的自适应识别

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Card-handling using hypertext editor can be a powerful methodology for generation of ideas or understanding of complex problems. To support such activity, recognizing implicit structure in the arrangement of cards would be useful. But, because the structures to be recognized are by nature ambiguous and highly dependent on user-specific perception, it is difficult for conventional rule-based spatial parsing algorithm to achieve this task. We propose techniques for building spatial parser suitable for finding such ambiguous structures based on the mechanics of human perception. Moreover, our parser is adaptively customized to reflect a particular user's preferences through an interactive suggestion process, supported by application of a genetic algorithm.
机译:使用超文本编辑器进行卡片处理可能是产生想法或理解复杂问题的强大方法。为了支持这种活动,识别卡片排列中的隐式结构将很有用。但是,由于要识别的结构本质上是模棱两可的,并且高度依赖于用户特定的感知,因此常规的基于规则的空间解析算法很难实现此任务。我们提出了一种构建空间解析器的技术,该技术适合于基于人类感知的机制来找到这种模糊的结构。此外,我们的解析器经过自适应定制,可以通过遗传算法的应用支持的交互式建议过程来反映特定用户的偏好。

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