User centered and ontology based information retrieval system for life sciences

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• 作者：Mohameth-Fran?ois Sy (1)
  Sylvie Ranwez (1)
  Jacky Montmain (1)
  Armelle Regnault (2)
  Michel Crampes (1)
  Vincent Ranwez (3)
  
• 刊名：BMC Bioinformatics
• 出版年：2012
• 出版时间：December 2012
• 年：2012
• 卷：13
• 期：1-supp
• 全文大小：798KB
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• 作者单位：Mohameth-Fran?ois Sy (1)
  Sylvie Ranwez (1)
  Jacky Montmain (1)
  Armelle Regnault (2)
  Michel Crampes (1)
  Vincent Ranwez (3)
  
  1. LGI2P Research Centre, EMA/Site EERIE, Parc scientifique G. Besse, 30 035, N?mes cedex 1, France
  2. Inserm/Institut Multi-Organismes, Immunologie, Hématologie et Pneumologie (ITMO IHP), 175, rue du Chevaleret, 75013, Paris, France
  3. Institut des Sciences de l’Evolution de Montpellier (ISE-M), UMR 5554 CNRS Université Montpellier II, place E. Bataillon, CC 064, 34 095, Montpellier cedex 05, France
  
• ISSN：1471-2105

文摘

Background Because of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life science, for instance, the Gene Ontology is widely exploited in genomic applications and the Medical Subject Headings is the basis of biomedical publications indexation and information retrieval process proposed by PubMed. However current search engines suffer from two main drawbacks: there is limited user interaction with the list of retrieved resources and no explanation for their adequacy to the query is provided. Users may thus be confused by the selection and have no idea on how to adapt their queries so that the results match their expectations. Results This paper describes an information retrieval system that relies on domain ontology to widen the set of relevant documents that is retrieved and that uses a graphical rendering of query results to favor user interactions. Semantic proximities between ontology concepts and aggregating models are used to assess documents adequacy with respect to a query. The selection of documents is displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user's query; this man/machine interface favors a more interactive and iterative exploration of data corpus, by facilitating query concepts weighting and visual explanation. We illustrate the benefit of using this information retrieval system on two case studies one of which aiming at collecting human genes related to transcription factors involved in hemopoiesis pathway. Conclusions The ontology based information retrieval system described in this paper (OBIRS) is freely available at: http://www.ontotoolkit.mines-ales.fr/ObirsClient/. This environment is a first step towards a user centred application in which the system enlightens relevant information to provide decision help.