Exploring semantic groups through visual approaches
Exploring semantic groups through visual approaches
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DOI：
10.1016/j.jbi.2003.11.002
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发表时间：
2003-12-01
影响因子：
4.5
通讯作者：
McCray, AT
中科院分区：
文献类型：
--
作者：
Bodenreider, O;McCray, AT
目标.我们研究了几种可视化的方法来探索语义组，一组语义类型的统一医学语言系统（UMLS）的语义网络。我们特别感兴趣的语义连贯性的群体，我们使用的语义关系作为重要指标的连贯性。首先，我们创建一个径向表示的数量之间的关系组，为每个语义组生成一个配置文件。其次，我们表明，在我们的分区，组织的关系围绕有限数量的枢轴组和随机创建的分区不表现出此属性。最后，我们使用对应分析来可视化语义类型和关系之间的关联所产生的分组。这三种方法提供了不同的观点的语义组，并帮助检测潜在的不一致。它们使异常值立即变得明显，因此，它们可以作为审核和验证语义网络和语义组的工具。(C)2003年爱思唯尔公司All rights reserved.
Objectives. We investigate several visual approaches for exploring semantic groups, a grouping of semantic types from the Unified Medical Language System (UMLS) semantic network. We are particularly interested in the semantic coherence of the groups, and we use the semantic relationships as important indicators of that coherence.Methods. First, we create a radial representation of the number of relationships among the groups, generating a profile for each semantic group. Second, we show that, in our partition, the relationships are organized around a limited number of pivot groups and that partitions created at random do not exhibit this property. Finally, we use correspondence analysis to visualize groupings resulting from the association between semantic types and the relationships.Results. The three approaches provide different views on the semantic groups and help detect potential inconsistencies. They make outliers immediately apparent, and, thus, serve as a tool for auditing and validating both the semantic network and the semantic groups. (C) 2003 Elsevier Inc. All rights reserved.