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Using the OntoGene pipeline for the triage task of BioCreative 2012


Rinaldi, Fabio; Clematide, Simon; Hafner, Simon; Schneider, Gerold; Grigonyte, Gintare; Romacker, Martin; Vachon, Therese (2013). Using the OntoGene pipeline for the triage task of BioCreative 2012. Database, 2013:bas053.

Abstract

In this article, we describe the architecture of the OntoGene Relation mining pipeline and its application in the triage task of BioCreative 2012. The aim of the task is to support the triage of abstracts relevant to the process of curation of the Comparative Toxicogenomics Database. We use a conventional information retrieval system (Lucene) to provide a baseline ranking, which we then combine with information provided by our relation mining system, in order to achieve an optimized ranking. Our approach additionally delivers domain entities mentioned in each input document as well as candidate relationships, both ranked according to a confidence score computed by the system. This information is presented to the user through an advanced interface aimed at supporting the process of interactive curation. Thanks, in particular, to the high-quality entity recognition, the OntoGene system achieved the best overall results in the task.

In this article, we describe the architecture of the OntoGene Relation mining pipeline and its application in the triage task of BioCreative 2012. The aim of the task is to support the triage of abstracts relevant to the process of curation of the Comparative Toxicogenomics Database. We use a conventional information retrieval system (Lucene) to provide a baseline ranking, which we then combine with information provided by our relation mining system, in order to achieve an optimized ranking. Our approach additionally delivers domain entities mentioned in each input document as well as candidate relationships, both ranked according to a confidence score computed by the system. This information is presented to the user through an advanced interface aimed at supporting the process of interactive curation. Thanks, in particular, to the high-quality entity recognition, the OntoGene system achieved the best overall results in the task.

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3 citations in Web of Science®
4 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Date:2013
Deposited On:28 Mar 2013 10:04
Last Modified:05 Apr 2016 16:39
Publisher:Oxford University Press
ISSN:1758-0463
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/database/bas053
Permanent URL: https://doi.org/10.5167/uzh-75912

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