Sistemas de recuperación de información adaptados al dominio biomédico

The terminology used in biomedicine has lexical characteristics that have required the elaboration of terminological resources and information retrieval systems with specific functionalities. The main characteristics are the high rates of synonymy and homonymy, due to phenomena such as the proliferation of polysemic acronyms and their interaction with common language. Information retrieval systems in the biomedical domain use techniques oriented to the treatment of these lexical peculiarities. In this paper we review some of these techniques, such as the application of Natural Language Processing (BioNLP), the incorporation of lexical-semantic resources, and the application of Named Entity Recognition (BioNER). Finally, we present the evaluation methods adopted to assess the suitability of these techniques for retrieving biomedical resources.

[1]  O. Sánchez.  El Profesional de la información , 1997 .

[2]  Nigel Collier,et al.  A multilingual ontology for infectious disease surveillance: rationale, design and challenges , 2007, Lang. Resour. Evaluation.

[3]  Ricardo Baeza-Yates,et al.  Tendencias en minería de datos de la Web , 2009 .

[4]  Matthias Samwald,et al.  The bio-zen plus ontology , 2008, Appl. Ontology.

[5]  Thierry Poibeau,et al.  Proper Name Extraction from Non-Journalistic Texts , 2000, CLIN.

[6]  Alexander A. Morgan,et al.  Investigation of Unsupervised Pattern Learning Techniques for Bootstrap Construction of a Medical Treatment Lexicon , 2009, BioNLP@HLT-NAACL.

[7]  Nigel Collier,et al.  The development of a schema for semantic annotation: Gain brought by a formal ontological method , 2009, Appl. Ontology.

[8]  Sophia Ananiadou,et al.  Text Mining for Biology And Biomedicine , 2005 .

[9]  Peter Willett,et al.  Protein Structures and Information Extraction from Biological Texts: The PASTA System , 2003, Bioinform..

[10]  K. Bretonnel Cohen,et al.  Proceedings of the BioNLP 2009 Workshop , 2009 .

[11]  William R. Hersh,et al.  A survey of current work in biomedical text mining , 2005, Briefings Bioinform..

[12]  Andrew B. Clegg,et al.  Evaluating and Integrating Treebank Parsers on a Biomedical Corpus , 2005, ACL 2005.

[13]  Ulf Leser,et al.  What makes a gene name? Named entity recognition in the biomedical literature , 2005, Briefings Bioinform..

[14]  Christian Jacquemin,et al.  Spotting and Discovering Terms through Natural Language Processing , 1997 .

[15]  Sophia Ananiadou,et al.  A Flexible Measure of Contextual Similarity for Biomedical Terms , 2004, Pacific Symposium on Biocomputing.

[16]  Jian Su,et al.  Recognizing Names in Biomedical Texts: a Machine Learning Approach , 2004 .

[17]  Elena Beisswanger,et al.  BioTop and ChemTop - Top-Domain Ontologies for Biology and Chemistry , 2008, International Semantic Web Conference.

[18]  Jun'ichi Tsujii,et al.  Improving the performance of dictionary-based approaches in protein name recognition , 2004, J. Biomed. Informatics.

[19]  Barry Smith,et al.  A Strategy for Improving and Integrating Biomedical Ontologies , 2005, AMIA.

[20]  Olivier Bodenreider,et al.  The lexical properties of the gene ontology , 2002, AMIA.

[21]  Marc Weeber,et al.  Text-based discovery in biomedicine: the architecture of the DAD-system , 2000, AMIA.

[22]  Ross D King,et al.  Are the current ontologies in biology good ontologies? , 2005, Nature Biotechnology.

[23]  Hamish Cunningham,et al.  Information Extraction, Automatic , 2006 .

[24]  Hongfang Liu,et al.  Research Paper: Automatic Resolution of Ambiguous Terms Based on Machine Learning and Conceptual Relations in the UMLS , 2002, J. Am. Medical Informatics Assoc..

[25]  Lawrence Hunter,et al.  Pacific symposium on biocomputing 2006 , 2005, PSB 2016.

[26]  Olivier Bodenreider,et al.  Chapter 3 Lexical, terminological and ontological resources for biological text mining , 2006 .

[27]  Anand Kumar,et al.  Text mining and ontologies in biomedicine: Making sense of raw text , 2005, Briefings Bioinform..

[28]  Malvina Nissim,et al.  A System for Identifying Named Entities in Biomedical Text: how Results From two Evaluations Reflect on Both the System and the Evaluations , 2005, Comparative and functional genomics.

[29]  Alexander A. Morgan,et al.  Gene name identification and normalization using a model organism database , 2004, J. Biomed. Informatics.