BioLemmatizer: a lemmatization tool for morphological processing of biomedical text.
BioLemmatizer: a lemmatization tool for morphological processing of biomedical text.
复制标题
DOI：
10.1186/2041-1480-3-3
复制
发表时间：
2012-04-01
影响因子：
1.9
通讯作者：
Verspoor K
中科院分区：
文献类型：
--
作者：
Liu H;Christiansen T;Baumgartner WA Jr;Verspoor K
领域特定技术术语的各种形态变体增加了对与分子生物学相关的科学文献进行自然语言处理的复杂性。为了对这些文本进行形态学分析，鳞片化在近年来的生物医学研究中得到了积极的应用。在这项工作中，我们开发了一个特定领域的词形化工具，BioLemmatizer，用于生物医学文献的形态学分析。该工具侧重于英语的屈折形态，并基于通用英语词形化工具MorphAdorner。BioLemmatizer通过整合几个已发表的词汇资源进一步针对生物领域进行了定制。它根据单词词典的使用情况检索词，并定义一组规则，在词典中没有遇到词时将其转换为词。BioLemmatizer的一个创新之处在于使用分层策略搜索词典，即使输入的词性信息不准确，也能发现正确的引理。BioLemmatizer在对CRAFT语料库（一个生物医学全文文章的集合）编制的评估集进行归纳时，准确率达到97.5%，在LLL05语料库上的准确率达到97.6%。当BioLemmatizer作为生物医学文本挖掘系统的一个组件使用时，进一步证明了它对提高实际信息提取任务的准确性的贡献。BioLemmatizer与八种现有的lemmatizer相比，性能优于其他工具。BioLemmatizer作为开源软件发布，可以从http://biolemmatizer.sourceforge.net下载。
The wide variety of morphological variants of domain-specific technical terms contributes to the complexity of performing natural language processing of the scientific literature related to molecular biology. For morphological analysis of these texts, lemmatization has been actively applied in the recent biomedical research. In this work, we developed a domain-specific lemmatization tool, BioLemmatizer, for the morphological analysis of biomedical literature. The tool focuses on the inflectional morphology of English and is based on the general English lemmatization tool MorphAdorner. The BioLemmatizer is further tailored to the biological domain through incorporation of several published lexical resources. It retrieves lemmas based on the use of a word lexicon, and defines a set of rules that transform a word to a lemma if it is not encountered in the lexicon. An innovative aspect of the BioLemmatizer is the use of a hierarchical strategy for searching the lexicon, which enables the discovery of the correct lemma even if the input Part-of-Speech information is inaccurate. The BioLemmatizer achieves an accuracy of 97.5% in lemmatizing an evaluation set prepared from the CRAFT corpus, a collection of full-text biomedical articles, and an accuracy of 97.6% on the LLL05 corpus. The contribution of the BioLemmatizer to accuracy improvement of a practical information extraction task is further demonstrated when it is used as a component in a biomedical text mining system. The BioLemmatizer outperforms other tools when compared with eight existing lemmatizers. The BioLemmatizer is released as an open source software and can be downloaded from http://biolemmatizer.sourceforge.net.
登录
查看更多内容
影响因子：
7
作者：
Ashburner, M;Ball, CA;Yoon, J
通讯作者：
Yoon, J
影响因子：
3
作者：
Kim JD;Ohta T;Tsujii J
通讯作者：
Tsujii J
影响因子：
5.8
作者：
Kim, J-D;Ohta, T.;Tsujii, J.
通讯作者：
Tsujii, J.
影响因子：
3.7
作者：
Cohen KB;Palmer M;Hunter L
通讯作者：
Hunter L