title: Mining knowledge from corpora: an application to retrieval and indexing.
abstract: The present work aims at discovering new associations between medical concepts to be exploited as input in retrieval and indexing.
  
  
  METHODS
  Association rules method is applied to documents. The process is carried out on three major document categories referring to e-health information consumers: health professionals, students and lay people. Association rules evaluation is founded on statistical measures combined with domain knowledge.
  
  
  RESULTS
  Association rules represent existing relations between medical concepts (60.62%) and new knowledge (54.21%). Based on observations, 463 expert rules are defined by medical librarians for retrieval and indexing.
  
  
  CONCLUSIONS
  Association rules bear out existing relations, produce new knowledge and support users and indexers in document retrieval and indexing.
authors.affiliation: LIM&Bio EA 3969, SMBH Léonard de Vinci, Paris XIII University, Bobigny, France. lina.soualmia@gmail.com
authors.forename: Lina F
authors.initials: LF
authors.lastname: Soualmia
authors.forename: Badisse
authors.initials: B
authors.lastname: Dahamna
authors.forename: Stéfan
authors.initials: S
authors.lastname: Darmoni
mesh_terms: D000043:Abstracting and Indexing; D054626:Consumer Health Information; D005103:Expert Systems; D005602:France; D006801:Humans; D016247:Information Storage and Retrieval; D020407:Internet; D007993:Libraries, Medical; D046650:Medical Subject Headings; D009323:Natural Language Processing; D017432:Unified Medical Language System; D018875:Vocabulary, Controlled