Abstract
This paper introduces ConQuR-Bio which aims at assisting scientists when they query public biological databases. Various reformulations of the user query are generated using medical terminologies. Such alternative reformulations are then used to rank the query results using a new consensus ranking strategy. The originality of our approach thus lies in using consensus ranking techniques within the context of query reformulation. The ConQuR-Bio system is able to query the EntrezGene NCBI database. Our experiments demonstrate the benefit of using ConQuR-Bio compared to what is currently provided to users. ConQuR-Bio is available to the bioinformatics community at http://conqur-bio.lri.fr .
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Brancotte, B., Rance, B., Denise, A., Cohen-Boulakia, S. (2014). ConQuR-Bio: Consensus Ranking with Query Reformulation for Biological Data. In: Galhardas, H., Rahm, E. (eds) Data Integration in the Life Sciences. DILS 2014. Lecture Notes in Computer Science(), vol 8574. Springer, Cham. https://doi.org/10.1007/978-3-319-08590-6_13
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DOI: https://doi.org/10.1007/978-3-319-08590-6_13
Publisher Name: Springer, Cham
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