Computer and Information Sciences
University of Delaware
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| AUTHOR: |
Manabu Torii and Sachin Kamboj and K. Vijay-Shanker
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| TITLE: |
Using name-internal and contextual features to classify biological terms
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| ABSTRACT: |
There has been considerable work done recently in
recognizing named entities in biomedical text. In
this paper, we investigate the named entity
classification task, an integral part of the named
entity extraction task. We focus on the different
sources of information that can be utilized for
classification, and note the extent to which they
are effective in classification. To classify a name, we consider features that appear within the name as
well as nearby phrases. We also develop a new
strategy based on the context of occurrence and show
that they improve the performance of the
classification system. We show how our work relates
to previous works on named entity classification in
the biological domain as well as to those in generic
domains. The experiments were conducted on the GENIA
corpus Ver. 3.0 developed at University of Tokyo. We
achieve f value of 86 in 10-fold cross validation
evaluation on this corpus.
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| KEYWORDS: |
Name Classification, Name Entity Extraction, Biomedical Names, Information Sources
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| PUBLICATION: |
Journal of Biomedical Informatics
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| DATE: |
December, 2004
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| SOURCES: |
PDF: http://www.cis.udel.edu/~kamboj/pubs/kamboj.jbi.04.pdf
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| PAGES: |
498-511
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| NUMBER: |
6
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| VOLUME: |
37
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| BIBTEX: |
@article{kamboj.jbi.04, Author = {Manabu Torii and Sachin Kamboj and K. Vijay-Shanker}, Pages = {498-511}, Title = {Using name-internal and contextual features to classify biological terms}, Number = {6}, Month = {December}, Volume = {37}, Year = {2004}, Keywords = {Name Classification, Name Entity Extraction, Biomedical Names, Information Sources}, Journal = {Journal of Biomedical Informatics}, } |
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