Solbrig H R, Elkin P L, Ogren P V, Chute C G
Mayo Clinic, Rochester, MN, USA.
Proc AMIA Symp. 2000:814-8.
Medical terminologies continue to grow in scope, completeness and detail. The emerging generation of terminology systems define concepts in terms of their position within a categorical structure. It is still necessary, however, to access and represent the concepts using everyday spoken and written language, which introduces both lexical and semantic ambiguity. This ambiguity can have a negative impact on both selectivity and recall when it comes to associating free-form textual phrases with their coded equivalent. Lexical ambiguity issues can often be addressed algorithmically, but semantic ambiguity presents a more difficult problem. A common solution to the semantic problem is to associate many different representational permutations with a given target concept. This approach has several drawbacks. An alternate solution is to build separate synonym tables that can serve as permuted indices into the terms representing the underlying concepts. A potential shortcoming of this approach, however, is a further reduction in the lookup selectivity. One possible source of loss of selectivity could be "meaning drift"--the gradual change in meaning that can be introduced when following a chain of nearly synonymous words. We posited that organizing synonyms into separate "meaning clusters" might reduce this loss in precision, but the results of this study did not bear that out.
医学术语在范围、完整性和细节方面不断发展。新一代术语系统根据概念在分类结构中的位置来定义概念。然而，使用日常口语和书面语言来获取和表示这些概念仍然是必要的，这就引入了词汇和语义上的歧义。当涉及到将自由形式的文本短语与其编码等价物相关联时，这种歧义会对选择性和召回率产生负面影响。词汇歧义问题通常可以通过算法解决，但语义歧义则是一个更棘手的问题。解决语义问题的常见方法是将许多不同的表示排列与给定的目标概念相关联。这种方法有几个缺点。另一种解决方案是构建单独的同义词表，这些表可以作为进入表示基础概念的术语的排列索引。然而，这种方法的一个潜在缺点是查找选择性的进一步降低。选择性损失的一个可能来源可能是“意义漂移”——在遵循一系列近乎同义词时可能引入的意义逐渐变化。我们假设将同义词组织成单独的“意义簇”可能会减少这种精度损失，但这项研究的结果并未证实这一点。
