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Combining multiple disambiguation methods for gene mention normalization
Abstract The rapid growth of biomedical literature The rapid growth of biomedical literature prompts pervasive concentrations of biomedical text mining community to explore methodology for accessing and managing this ever-increasing knowledge. One important task of text mining in biomedical literature is gene mention normalization which recognizes the biomedical entities in biomedical texts and maps each gene mention discussed in the text to unique organic database identifiers. In this work, we employ an information retrieval based method which extracts gene mention's semantic profile from PubMed abstracts for gene mention disambiguation. This disambiguation method focuses on generating a more comprehensive representation of gene mention rather than the organic clues such as gene ontology which has fewer co-occurrences with the gene mention. Furthermore, we use an existing biomedical resource as another disambiguation method. Then we extract features from gene mention detection system's outcome to build a false positive filter according to Wikipedia's retrieved documents. Our system achieved F-measure of 83.1% on BioCreative II GN test data. © 2011 Elsevier Ltd. All rights reserved. © 2011 Elsevier Ltd. All rights reserved.
Abstractsub The rapid growth of biomedical literature The rapid growth of biomedical literature prompts pervasive concentrations of biomedical text mining community to explore methodology for accessing and managing this ever-increasing knowledge. One important task of text mining in biomedical literature is gene mention normalization which recognizes the biomedical entities in biomedical texts and maps each gene mention discussed in the text to unique organic database identifiers. In this work, we employ an information retrieval based method which extracts gene mention's semantic profile from PubMed abstracts for gene mention disambiguation. This disambiguation method focuses on generating a more comprehensive representation of gene mention rather than the organic clues such as gene ontology which has fewer co-occurrences with the gene mention. Furthermore, we use an existing biomedical resource as another disambiguation method. Then we extract features from gene mention detection system's outcome to build a false positive filter according to Wikipedia's retrieved documents. Our system achieved F-measure of 83.1% on BioCreative II GN test data. © 2011 Elsevier Ltd. All rights reserved. © 2011 Elsevier Ltd. All rights reserved.
Bibtextype article  +
Doi 10.1016/j.eswa.2010.12.106  +
Has author Xia N. + , Hong Lin + , Zhenglu Yang + , Yanyan Li +
Has extra keyword BioCreative II + , Biomedical literature + , Biomedical resource + , Biomedical text + , Biomedical text minings + , Detection system + , Disambiguation method + , F-measure + , False positive + , Gene ontology + , Rapid growth + , Retrieved documents + , Test data + , Text mining + , Web-based kernel + , Wikipedia + , Character recognition + , Filtration + , Information retrieval + , Natural language processing systems + , Ontology + , Semantics + , Genes +
Has keyword BioCreative II + , Gene mention normalization + , Gene symbol disambiguation + , Web-based kernel +
Issn 9574174  +
Issue 7  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 7994–7999  +
Published in Expert Systems with Applications +
Title Combining multiple disambiguation methods for gene mention normalization +
Type journal article  +
Volume 38  +
Year 2011 +
Creation dateThis property is a special property in this wiki. 7 November 2014 05:16:57  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Journal articles  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 05:16:57  +
DateThis property is a special property in this wiki. 2011  +
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