Hybrid Text Mining for Finding Abbreviations and their Definitions
Hybrid Text Mining for Finding Abbreviations and their Definitions
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DOI：
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发表时间：
2001
影响因子：
6.6
通讯作者：
Youngja Park;Roy J. Byrd
中科院分区：
文献类型：
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作者：
Youngja Park;Roy J. Byrd
提出了一种用于在自由格式文本中查找缩略语及其定义的混合文本挖掘方法。为了解决这个问题，该方法除了使用文本标记和提示词外，还使用了基于模式的缩写规则。基于模式的规则描述了如何从定义形成缩写。规则可以自动和/或手动生成，并且可以在系统处理新文档时进行扩充。该方法具有精度高、灵活性强、覆盖范围广、识别速度快等优点。
We present a hybrid text mining method for finding abbreviations and their definitions in free format texts. To deal with the problem, this method employs pattern-based abbreviation rules in addition to text markers and cue words. The pattern-based rules describe how abbreviations are formed from definitions. Rules can be generated automatically and/or manually and can be augmented when the system processes new documents. The proposed method has the advantages of high accuracy, high flexibility, wide coverage, and fast recognition.