title: USI: a fast and accurate approach for conceptual document annotation.
abstract: BACKGROUND
  Semantic approaches such as concept-based information retrieval rely on a corpus in which resources are indexed by concepts belonging to a domain ontology. In order to keep such applications up-to-date, new entities need to be frequently annotated to enrich the corpus. However, this task is time-consuming and requires a high-level of expertise in both the domain and the related ontology. Different strategies have thus been proposed to ease this indexing process, each one taking advantage from the features of the document.
  
  
  RESULTS
  In this paper we present USI (User-oriented Semantic Indexer), a fast and intuitive method for indexing tasks. We introduce a solution to suggest a conceptual annotation for new entities based on related already indexed documents. Our results, compared to those obtained by previous authors using the MeSH thesaurus and a dataset of biomedical papers, show that the method surpasses text-specific methods in terms of both quality and speed. Evaluations are done via usual metrics and semantic similarity.
  
  
  CONCLUSIONS
  By only relying on neighbor documents, the User-oriented Semantic Indexer does not need a representative learning set. Yet, it provides better results than the other approaches by giving a consistent annotation scored with a global criterion - instead of one score per concept.
authors.affiliation: LGI2P research center from the Ecole des mines d'Alès, Site de Nîmes, Parc scientifique G. Besse, Nîmes cedex 1, 30035, France. nicolas.fiorini@mines-ales.fr.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Fiorini
authors.affiliation: LGI2P research center from the Ecole des mines d'Alès, Site de Nîmes, Parc scientifique G. Besse, Nîmes cedex 1, 30035, France. sylvie.ranwez@mines-ales.fr.
authors.forename: Sylvie
authors.initials: S
authors.lastname: Ranwez
authors.affiliation: LGI2P research center from the Ecole des mines d'Alès, Site de Nîmes, Parc scientifique G. Besse, Nîmes cedex 1, 30035, France. jacky.montmain@mines-ales.fr.
authors.forename: Jacky
authors.initials: J
authors.lastname: Montmain
authors.affiliation: UMR AGAP, Montpellier SupAgro/CIRAD/INRA, 2 place Pierre Viala, Montpellier Cedex 1, 34060, France. ranwez@supagro.inra.fr.
authors.forename: Vincent
authors.initials: V
authors.lastname: Ranwez
mesh_terms: D000043:Abstracting and Indexing; D000465:Algorithms; D006801:Humans; D016247:Information Storage and Retrieval; D046650:Medical Subject Headings; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated; D012660:Semantics; D014584:User-Computer Interface; D018875:Vocabulary, Controlled