title: Using the OntoGene pipeline for the triage task of BioCreative 2012.
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.
authors: Institute of Computational Linguistics, University of Zurich, Binzmuhlestrasse 14, Zurich 8050, Switzerland. fabio.rinaldi@uzh.ch
authors: Fabio
authors: F
authors: Rinaldi
authors: Simon
authors: S
authors: Clematide
authors: Simon
authors: S
authors: Hafner
authors: Gerold
authors: G
authors: Schneider
authors: Gintare
authors: G
authors: Grigonyte
authors: Martin
authors: M
authors: Romacker
authors: Therese
authors: T
authors: Vachon
mesh_terms: D057225:Data Mining / Q000379:methods*; D030541:Databases, Genetic; D016247:Information Storage and Retrieval; D058977:Molecular Sequence Annotation / Q000379:methods*; D043922:Toxicogenetics; D014584:User-Computer Interface
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