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Author Lin, Kevin Hsin-Yih ♦ Hou, Wen-Juan ♦ Chen, Hsin-Hsi
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Full-text Biomedical Article ♦ Gene Ontology Annotation ♦ Different Density Model ♦ Several Evaluation Criterion ♦ Density Function ♦ Word Proximity Relationship ♦ Go Term ♦ Gene-go Pair ♦ Gene Ontology
Description In this paper, we propose an approach for doing Gene Ontology (GO) annotation on full-text biomedical articles. This system explores the word proximity relationship between genes and GO terms. We associate genes and GO terms by considering the density function between gene-GO pairs in a paragraph. Different density models are built and several evaluation criteria are employed to assess the effects of the proposed methods. In the best case, we got a precision of < 88 % and a recall of < 12%. 1
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2006-01-01
Publisher Institution Proc. Second Int. Symp. Semantic Mining in Biomedicine, 44{51