| Download | - View accepted manuscript: Functional Annotation of Genes Using Hierarchical Text Categorization (PDF, 266 KiB)
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| Author | Search for: Kiritchenko, Svetlana; Search for: Matwin, S.; Search for: Famili, Fazel |
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| Format | Text, Article |
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| Conference | BioLINK SIG: Linking Literature, Information and Knowledge for Biology, a Joint Meeting of The ISMB BioLINK Special Interest Group on Text Data Mining and The ACL Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics to be held in conjunction with the Conference on Intelligent Systems for Molecular Biology (ISMB 2005), June 24, 2005, Detroit, Michigan, USA |
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| Abstract | This paper addresses the task of functional annotation of genes from biomedical literature. We view this task as a hierarchical text categorization problem with Gene Ontology as a class hierarchy. We present a novel global hierarchical learning approach that takes into account the semantics of a class hierarchy. This algorithm with AdaBoost as the underlying learning procedure significantly outperforms the corresponding flat” approach, i.e. the approach that does not consider any hierarchical information. In addition, we propose a novel hierarchical evaluation measure that gives credit to partially correct classification and discriminates errors by both distance and depth in a class hierarchy. |
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| Publication date | 2005 |
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| In | |
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| Language | English |
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| NRC number | NRCC 48063 |
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| NPARC number | 5763768 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 4681be12-118e-43be-8014-31379eb5aa98 |
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| Record created | 2009-03-29 |
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| Record modified | 2020-10-09 |
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