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Using Combinatory Categorial Grammar to Extract Biomedical Information
Oleh:
Park, J. C.
Jenis:
Article from Bulletin/Magazine
Dalam koleksi:
IEEE Intelligent Systems vol. 16 no. 6 (2001)
,
page 62-67.
Topik:
biomedical
;
combinatory categorial grammar
;
biomedical information
Ketersediaan
Perpustakaan Pusat (Semanggi)
Nomor Panggil:
II60.4
Non-tandon:
1 (dapat dipinjam: 0)
Tandon:
tidak ada
Lihat Detail Induk
Isi artikel
Extracting information from biology databases manually can be an overwhelming task. GenBank, the US National Institutes of Health database containing all publicly available DNA sequences, has more than 14 billion bases in 13 million genetic - sequence records. Medline, a literature database available through PubMed, has over 11 million journal citations. In a May 2001 search request for "cytokine" (regulatory proteins in the immune system), PubMed returned 296556 articles. Given the quantity and complexity of biomedical literature, demands for computational tools to extract specific information are increasing. The author reviews biomedical information extraction methods and presents research done by KAIST's natural language processing group on a system that shows encouraging performance using combinatory categorial grammar as a natural language grammar formalism.
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