Joubert M, Fieschi M, Robert J J, Tafazzoli A
CERTIM, Faculté de Médecine, Marseille, France.
Int J Biomed Comput. 1994 Oct;37(2):93-104. doi: 10.1016/0020-7101(94)90132-5.
As information databases we consider all the kinds of information repositories that are handled by computer systems. When querying very large information databases, the end-users are often faced with the problem to parse their questions efficiently into the query languages of the computer systems. Conceptual graphs were initially designed for natural language analysis and understanding. Due to their closeness to semantic networks, their expressiveness is powerful enough to be applied to knowledge representation and use by computer systems. This work demonstrates that conceptual graphs are a suitable means to model both the information in patient databases and the queries to these databases, and that operations on graphs can compute the pattern matching process needed to provide the answers. A prototype that exploits this model is presented. Experiments have been made with the material furnished by the Unified Medical Language System project (version 2, 1992) of the National Library of Medicine, USA.
作为信息数据库，我们考虑由计算机系统处理的所有类型的信息存储库。在查询非常大的信息数据库时，终端用户常常面临如何将他们的问题高效地解析为计算机系统查询语言的问题。概念图最初是为自然语言分析和理解而设计的。由于它们与语义网络相近，其表达能力强大到足以应用于计算机系统的知识表示和使用。这项工作表明，概念图是对患者数据库中的信息以及对这些数据库的查询进行建模的合适手段，并且图上的操作可以计算出提供答案所需的模式匹配过程。本文展示了一个利用该模型的原型。我们已经使用了美国国立医学图书馆统一医学语言系统项目（1992年第2版）提供的资料进行了实验。
