Perl Yehoshua, Chen Zong, Halper Michael, Geller James, Zhang Li, Peng Yi
Computer Science Department, New Jersey Institute of Technology, Newark, NJ 07102, USA.
J Biomed Inform. 2002 Jun;35(3):194-212. doi: 10.1016/s1532-0464(02)00528-2.
The Unified Medical Language System (UMLS) joins together a group of established medical terminologies in a unified knowledge representation framework. Two major resources of the UMLS are its Metathesaurus, containing a large number of concepts, and the Semantic Network (SN), containing semantic types and forming an abstraction of the Metathesaurus. However, the SN itself is large and complex and may still be difficult to view and comprehend. Our structural partitioning technique partitions the SN into structurally uniform sets of semantic types based on the distribution of the relationships within the SN. An enhancement of the structural partition results in cohesive, singly rooted sets of semantic types. Each such set is named after its root which represents the common nature of the group. These sets of semantic types are represented by higher-level components called metasemantic types. A network, called a metaschema, which consists of the meta-semantic types connected by hierarchical and semantic relationships is obtained and provides an abstract view supporting orientation to the SN. The metaschema is utilized to audit the UMLS classifications. We present a set of graphical views of the SN based on the metaschema to help in user orientation to the SN. A study compares the cohesive metaschema to metaschemas derived semantically by UMLS experts.
统一医学语言系统（UMLS）在一个统一的知识表示框架中整合了一组既定的医学术语。UMLS的两个主要资源是其元词表，其中包含大量概念，以及语义网络（SN），其中包含语义类型并形成元词表的抽象。然而，SN本身庞大且复杂，可能仍然难以查看和理解。我们的结构划分技术基于SN中关系的分布将SN划分为结构统一的语义类型集。对结构划分的增强会产生具有内聚性、单根的语义类型集。每个这样的集以其代表该组共同性质的根来命名。这些语义类型集由称为元语义类型的更高级组件表示。获得了一个由通过层次关系和语义关系连接的元语义类型组成的网络，称为元模式，它提供了一个支持对SN进行定向的抽象视图。该元模式用于审核UMLS分类。我们基于元模式展示了一组SN的图形视图，以帮助用户了解SN。一项研究将具有内聚性的元模式与UMLS专家通过语义推导得出的元模式进行了比较。
