%0 Journal Article %1 ValenciaGarcia:2008 %A Valencia-Garc\'ıa, Rafael %A Fernández-Breis, Jesualdo Tomás %A Ruiz-Mart\'ınez, Juana Mar\'ıa %A Garc\'ıa-Sánchez, Francisco %A Mart\'ınez-Béjar, Rodrigo %D 2008 %J Expert Systems %K information_retrieval retrieval ontology biomedical %N 3 %P 1-19 %T A Knowledge Acquisition Methodology to Ontology Construction for Information Retrieval from Medical Documents %V 25 %X Vast amounts of medical information reside within text documents, so that the automatic retrieval of such information would certainly be beneficial for clinical activities. The need for overcoming the bottleneck provoked by the manual construction of ontologies has generated several studies and reseach on obtaining semi-automatic methods to build ontologies. Most techniques for learning domain ontologies from free text have important limitations. Thus, they can extract concepts so that only taxonomies are generally produced although there are other types of semantic relations relevant in knowledge modelling. This paper presents a language-independent approach for extracting knowledge from medical natural language documents. The knoledge is represented by means of ontologies that can have multiple semantic relationships among concepts.

@article{ValenciaGarcia:2008, abstract = {Vast amounts of medical information reside within text documents, so that the automatic retrieval of such information would certainly be beneficial for clinical activities. The need for overcoming the bottleneck provoked by the manual construction of ontologies has generated several studies and reseach on obtaining semi-automatic methods to build ontologies. Most techniques for learning domain ontologies from free text have important limitations. Thus, they can extract concepts so that only taxonomies are generally produced although there are other types of semantic relations relevant in knowledge modelling. This paper presents a language-independent approach for extracting knowledge from medical natural language documents. The knoledge is represented by means of ontologies that can have multiple semantic relationships among concepts.}, added-at = {2009-07-06T09:49:33.000+0200}, author = {Valencia-Garc{\'\i}a, Rafael and Fern{\'a}ndez-Breis, Jesualdo Tom{\'a}s and Ruiz-Mart{\'\i}nez, Juana Mar{\'\i}a and Garc{\'\i}a-S{\'a}nchez, Francisco and Mart{\'\i}nez-B{\'e}jar, Rodrigo}, biburl = {https://www.bibsonomy.org/bibtex/22709bee9837d063247aaa2240dcdd538/diego_ma}, interhash = {d401afca26655ded4110a0aa02afe72e}, intrahash = {2709bee9837d063247aaa2240dcdd538}, journal = {Expert Systems}, keywords = {information_retrieval retrieval ontology biomedical}, library = {Mine (from Juani, July 2009)}, number = 3, pages = {1-19}, timestamp = {2009-07-06T09:49:33.000+0200}, title = {A Knowledge Acquisition Methodology to Ontology Construction for Information Retrieval from Medical Documents}, volume = 25, year = 2008 }