Normalization of gene/protein names in biological literatures using Vector-Space Model.
As the number of biological literatures grows exponentially, needs for text mining system are increased. In text mining area, normalization is mapping gene/protein names to a database. It is necessary to combine extracted information from various literatures and to create a database or an ontology using literatures. Previous normalization researches used direct comparison methods between a database and literatures, but it is weak to extremely variational gene/protein names in literatures. Therefore, in this paper, we propose a normalization method using Vector-Space Model. For each gene/protein name, we rank identifiers using Vector-Space Model, and find the most similar identifier with the name. Experimental result shows the proposed method has 70.7% f-measure.
Lim
Joon-Ho
JH
Lifeinformatics Team, Electronics and Telecommunication Research Institute, Gajeong-Dong, Yuseon-Gu, Daejeon, 305-700, Korea. joonho.lim@etri.re.kr
Jang
Hyunchul
H
Lim
Jaesoo
J
Park
Soo-Jun
SJ
D000043:Abstracting and Indexing; D030541:Databases, Genetic; D005796:Genes; D008962:Models, Theoretical; D011506:Proteins; D009626:Terminology as Topic
D011506:Proteins