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吴振新 |
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一种从医学文本中实现自动关键词抽取和筛选的技术方法*
殷蜀梅1 张智雄2 吴振新2
1（北京大学医学图书馆 北京 100083）
2（中国科学院国家科学图书馆 北京100190）
鉴于重要关键词对于文本有着重要的强文本表示功能，关键词抽取和筛选在信息检索、信息抽取和知识挖掘等领域中有着重要的作用。在调研当前关键词抽取的方法后，结合医学领域已有的叙词表和工具以及BM25F加权词频公式提出基于医学文本的重要关键词抽取和筛选的技术方法。该方法主要解决两个关键问题：关键词的识别和抽取、关键词重要性的衡量和筛选。以2001-2007年骨关节炎领域的文献集合为数据来源，对该技术方法进行实践尝试，并验证其实际有效性，为知识挖掘中的重要关键词抽取提供一个行之有效的途径。
A Method for Automatic Keyword Extraction and Filtration from Medical Texts
Yin Shumei1 Zhang Zhixiong2 Wu Zhenxin2
1 (Peking University Health Science Library, Beijing 100083,China)
2 (National Science Library, Chinese Academy of Sciences, Beijing 100190,China)
Seeing that the keyword or key phrase can represent the feature of text, keyword extraction and filtration has great significance for information retrieval, information extraction and knowledge discovery. This paper first investigates current keyword extraction methods. Then it uses existing thesaurus and tools in the medical field and BM25F model in proposing a method for keyword extraction and filtration from medical texts. The proposed method mainly solves two key problems:identification and extraction of keywords, evaluation of keyword value and filtration of keywords. This paper applies the method on documents in the field of osteoarthritis from the year 2001 to 2007, and verifies its effectiveness, which offers an effective way for extracting keywords in knowledge discovery.
G250.73
*本文系国家社会科学基金项目“从数字信息资源中实现知识抽取的理论和方法研究”(项目编号：05BTQ006)的研究成果之一。
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