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Coping with Imprecision During a Semi-automatic Conceptual Indexing Process

  • Nicolas Fiorini
  • Sylvie Ranwez
  • Jacky Montmain
  • Vincent Ranwez
Part of the Communications in Computer and Information Science book series (CCIS, volume 444)

Abstract

Concept-based information retrieval is known to be a powerful and reliable process. It relies on a semantically annotated corpus, i.e. resources indexed by concepts organized within a domain ontology. The conception and enlargement of such index is a tedious task, which is often a bottleneck due to the lack of (semi-)automated solutions. In this paper, we first introduce a solution to assist experts during the indexing process thanks to semantic annotation propagation. The idea is to let them position the new resource on a semantic map, containing already indexed resources and to propose an indexation of this new resource based on those of its neighbors. To further help users, we then introduce indicators to estimate the robustness of the indexation with respect to the indicated position and to the annotation homogeneity of nearby resources. By computing these values before any interaction, it is possible to visually inform users on their margins of error, therefore reducing the risk of having a non-optimal, thus unsatisfying, annotation.

Keywords

conceptual indexing semantic annotation propagation imprecision management semantic similarity man-machine interaction 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nicolas Fiorini
    • 1
  • Sylvie Ranwez
    • 1
  • Jacky Montmain
    • 1
  • Vincent Ranwez
    • 2
  1. 1.Centre de recherche LGI2P de l’école des mines d’Alès, Parc Scientifique Georges BesseNîmes cedex 1France
  2. 2.Montpellier SupAgro, UMR AGAPMontpellierFrance

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