Abstract：
:Protein name recognition aims to detect each and every protein names appearing in a PubMed abstract. The task is not simple, as the graphic word boundary (space separator) assumed in conventional preprocessing does not necessarily coincide with the protein name boundary. Such boundary disagreement caused by tokenization ambiguity has usually been ignored in conventional preprocessing of general English. In this paper, we argue that boundary disagreement poses serious limitations in biomedical English text processing, not to mention protein name recognition. Our key idea for dealing with the boundary disagreement is to apply techniques used in Japanese morphological analysis where there are no word boundaries. Having evaluated the proposed method with GENIA corpus 3.02, we obtain F-measure of 69.01 on a strict criterion and 79.32 on a relaxed criterion. The result is comparable to other published work in protein name recognition, without resorting to manually prepared ad hoc feature engineering. Further, compared to the conventional preprocessing, the use of morphological analysis as preprocessing improves the performance of protein name recognition and reduces the execution time.
journal_name
J Biomed Informjournal_title
Journal of biomedical informaticsauthors
Yamamoto K,Kudo T,Konagaya A,Matsumoto Ydoi
10.1016/j.jbi.2004.08.001keywords:
subject
Has Abstractpub_date
2004-12-01 00:00:00pages
471-82issue
6eissn
1532-0464issn
1532-0480pii
S1532-0464(04)00079-6journal_volume
37pub_type
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journal_title：Journal of biomedical informatics
pub_type： 杂志文章
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更新日期：2013-12-01 00:00:00
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journal_title：Journal of biomedical informatics
pub_type： 杂志文章
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pub_type： 杂志文章
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更新日期：2010-06-01 00:00:00
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journal_title：Journal of biomedical informatics
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pub_type： 临床试验,杂志文章,多中心研究
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