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Conceptual search in electronic patient record.

机译:在电子患者记录中的概念搜索。

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Search by content in a large corpus of free texts in the medical domain is, today, only partially solved. The so-called GREP approach (Get Regular Expression and Print), based on highly efficient string matching techniques, is subject to inherent limitations, especially its inability to recognize domain specific knowledge. Such methods oblige the user to formulate his or her query in a logical Boolean style; if this constraint is not fulfilled, the results are poor. The authors present an enhancement to string matching search by the addition of a light conceptual model behind the word lexicon. The new system accepts any sentence as a query and radically improves the quality of results. Efficiency regarding execution time is obtained at the expense of implementing advanced indexing algorithms in a pre-processing phase. The method is described and commented and a brief account of the results illustrates this paper.
机译:在医疗领域的一个大型免费文本中搜索内容是,今天只有部分解决。基于高效字符串匹配技术的所谓的Grep方法(GET正则表达和打印)受到固有的限制,尤其是无法识别域特定知识。这些方法迫使用户在逻辑布尔样式中制定他或她的查询;如果不符合此约束,则结果差。作者通过添加词词典后面的轻概念模型来提高串字符串匹配搜索。新系统接受任何句子作为查询,从根本上提高结果质量。在预处理阶段实现高级索引算法的费用获得了关于执行时间的效率。该方法描述和评论,结果简要说明了这篇论文。

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