Creación automática de sistemas de búsqueda de respuestas en dominios restringidos

• Autores: Katia Vila Rodríguez, José-Norberto Mazón López , Antonio Ferrández Rodríguez
• Localización: El profesional de la información, ISSN-e 1699-2407, ISSN 1386-6710, Vol. 21, Nº 1, 2012 (Ejemplar dedicado a: El futuro de la web), págs. 16-26
• Idioma: español
• DOI: 10.3145/epi.2012.ene.03
• Títulos paralelos:
  • Automatic generation of question answering systems in restricted domains
• Enlaces
  • Texto completo
• Resumen
  • español

    Los sistemas de búsqueda de respuestas (BR) se pueden considerar como potenciales sucesores de los buscadores tradicionales de información en la Web. Para que sean precisos deben adaptarse a dominios concretos mediante el uso de recursos semánticos adecuados. La adaptación no es una tarea trivial, ya que deben integrarse e incorporarse a sistemas de BR existentes varios recursos heterogéneos relacionados con un dominio restringido. Se presenta la herramienta Maraqa, cuya novedad radica en el uso de técnicas de ingeniería del software, como el desarrollo dirigido por modelos, para automatizar dicho proceso de adaptación a dominios restringidos. Se ha evaluado Maraqa mediante una serie de experimentos (sobre el dominio agrícola) que demuestran su viabilidad, mejorando en un 29,5% la precisión del sistema adaptado.

  • English

    Question answering (QA) applications can be considered as the potential successors to the traditional information retrieval on the Web. However, QA systems should be adapted to restricted domains for the sake of precision. This adaptation is not a trivial task, since several heterogeneous resources related to a restricted domain must be integrated into existing QA systems. This paper presents the Maraqa tool, whose novelty is the use of software engineering techniques such as model driven development to automate the adaptation process. It is worth noting that Maraqa has been evaluated through a set of experiments (within the agricultural domain) that demonstrate its applicability: the precision of the adapted QA system showed 29.5% improvement.

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