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A Distance for Partially Labeled Trees

机译:部分标记树的距离

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In a number of practical situations, data have structure and the relations among its component parts need to be coded with suitable data models. Trees are usually utilized for representing data for which hierarchical relations can be defined. This is the case in a number of fields like image analysis, natural language processing, protein structure, or music retrieval, to name a few. In those cases, procedures for comparing trees are very relevant. An approximate tree edit distance algorithm has been introduced for working with trees labeled only at the leaves. In this paper, it has been applied to handwritten character recognition, providing accuracies comparable to those by the most comprehensive search method, being as efficient as the fastest.
机译:在许多实际情况下,数据具有结构,其组成部分之间的关​​系需要用合适的数据模型进行编码。树通常用于表示可以定义层次关系的数据。在许多领域中就是这种情况,例如图像分析,自然语言处理,蛋白质结构或音乐检索等。在这些情况下,比较树的过程非常重要。已经引入了近似的树编辑距离算法,用于处理仅在叶子处标记的树。在本文中,它已被应用于手写字符识别,其准确性可与最全面的搜索方法相提并论,其效率与最快的一样。

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