title: Knowledge representation and management: benefits and challenges of the semantic web for the fields of KRM and NLP.
abstract: OBJECTIVE
  To summarize excellent current research in the field of knowledge representation and management (KRM).
  
  
  METHODS
  A synopsis of the articles selected for the IMIA Yearbook 2011 is provided and an attempt to highlight the current trends in the field is sketched.
  
  
  RESULTS
  This last decade, with the extension of the text-based web towards a semantic-structured web, NLP techniques have experienced a renewed interest in knowledge extraction. This trend is corroborated through the five papers selected for the KRM section of the Yearbook 2011. They all depict outstanding studies that exploit NLP technologies whenever possible in order to accurately extract meaningful information from various biomedical textual sources.
  
  
  CONCLUSIONS
  Bringing semantic structure to the meaningful content of textual web pages affords the user with cooperative sharing and intelligent finding of electronic data. As exemplified by the best paper selection, more and more advanced biomedical applications aim at exploiting the meaningful richness of free-text documents in order to generate semantic metadata and recently to learn and populate domain ontologies. These later are becoming a key piece as they allow portraying the semantics of the Semantic Web content. Maintaining their consistency with documents and semantic annotations that refer to them is a crucial challenge of the Semantic Web for the coming years.
authors.affiliation: University Hospitals of Geneva, Information Systems Division, 4, Geneva, Switzerland. anne-marie.rassinoux@hcuge.ch
authors.forename: A-M
authors.initials: AM
authors.lastname: Rassinoux
mesh_terms: D020407:Internet; D058436:Knowledge Management; D009323:Natural Language Processing; D012660:Semantics