Context and Keyword Extraction in Plain Text Using a Graph Representation

Carlo Abi Chahine (1) , Nathalie Chaignaud (1) , Jean-Philippe Kotowicz (1) , Jean-Pierre Pécuchet (1)

1 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes

Document indexation is an essential task achieved by archivists or automatic indexing tools. To retrieve relevant documents to a query, keywords describing this document have to be carefully chosen. Archivists have to find out the right topic of a document before starting to extract the keywords. For an archivist indexing specialized documents, experience plays an important role. But indexing documents on different topics is much harder. This article proposes an innovative method for an indexing support system. This system takes as input an ontology and a plain text document and provides as output contextualized keywords of the document. The method has been evaluated by exploiting Wikipedia's category links as a termino-ontological resources.

Mots clés: Graph; Knowledge representation; Web semantic

Domaines: Recherche d'information [cs.IR]

Carlo Abi Chahine, Nathalie Chaignaud, Jean-Philippe Kotowicz, Jean-Pierre Pécuchet. Context and Keyword Extraction in Plain Text Using a Graph Representation. IEEE International Conference on Signal Image Technology and Internet Based Systems, SITIS '08., Nov 2008, Bali, Indonesia. pp.692-696. ⟨hal-00439215⟩