A light knowledge model for linguistic applications
A light knowledge model for linguistic applications
复制标题
语言应用的轻知识模型
DOI：
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发表时间：
2001
期刊：
影响因子：
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通讯作者：
A. Rassinoux
中科院分区：
文献类型：
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作者：
R. Baud;C. Lovis;Patrick Ruch;A. Rassinoux
今天，只要有足够的领域知识，从医学文本中提取内容是可以通过语言应用实现的。这种知识代表了该领域的一种模型，尽管尝试了许多次，但很难以足够的深度和良好的覆盖面收集到这些知识。利用这项任务是优先事项，以便从期待已久的语言工具中获益。灯光模型的设计考虑到了这一目标。句法和词汇信息通常在大词典中可用。领域模型应该添加必要的语义信息。在已识别的句法和词汇属性的基础上，设计了一个用于语义信息收集的轻量级知识模型。它是为获取足够的语义信息而定制的，以便从自由文本中检索受控词汇的术语，例如，从患者记录中检索网状术语。
Content extraction from medical texts is achievable today by linguistic applications, in so far as sufficient domain knowledge is available. Such knowledge represents a model of the domain and is hard to collect with sufficient depth and good coverage, despite numerous attempts. To leverage this task is a priority in order to benefit from the awaited linguistic tools. The light model is designed with this goal in mind. Syntactic and lexical information are generally available with large lexicons. A domain model should add the necessary semantic information. The authors have designed a light knowledge model for the collection of semantic information on the basis of the recognized syntactical and lexical attributes. It has been tailored for the acquisition of enough semantic information in order to retrieve terms of a controlled vocabulary from free texts, as for example, to retrieve Mesh terms from patient records.
DOI：
10.1016/0010-4809(91)90035-u
发表时间：
1991-07
期刊：
Computers and biomedical research, an international journal
影响因子：
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作者：
Fred P. Masarie;R. Miller;O. Bouhaddou;N. Giuse;H. Warner
通讯作者：
Fred P. Masarie;R. Miller;O. Bouhaddou;N. Giuse;H. Warner