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. © 2014 Springer International Publishing Switzerland.
Cite
CITATION STYLE
Brancotte, B., Rance, B., Denise, A., & Cohen-Boulakia, S. (2014). ConQuR-Bio: Consensus ranking with query reformulation for biological data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8574 LNBI, pp. 128–142). Springer Verlag. https://doi.org/10.1007/978-3-319-08590-6_13
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
