Conceptual Indexing for Multilingual Information Retrieval

  • Jacques Guyot
  • Saïd Radhouani
  • Gilles Falquet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4022)


We present a translation-free technique for multilingual information retrieval. This technique is based on an ontological representation of documents and queries. For each language, we use a dictionary (set of lexical reference for concepts) to map a term to its corresponding concept. The same mapping is applied to each document and each query. Then, we use a classic vector space model based on concept for indexing and querying the document corpus. The main advantages of our approach are: no merging phase is required; no dependency on automatic translators between all pairs of languages; and adding a new language only requires a new mapping dictionary to be added into the multilingual ontology. Experimental results on the CLEF 2005 multi8 collection show that this approach is efficient, even with relatively small and low fidelity dictionaries and without word sense disambiguation.


Query Language Mean Average Precision Vector Space Model Word Sense Disambiguation Original Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jacques Guyot
    • 1
  • Saïd Radhouani
    • 1
  • Gilles Falquet
    • 1
  1. 1.Centre Universitaire d’InformatiqueUniversity of GenevaGenève 4Switzerland

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