TAAABLE: Text Mining, Ontology Engineering, and Hierarchical Classification for Textual Case-Based Cooking - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2008

TAAABLE: Text Mining, Ontology Engineering, and Hierarchical Classification for Textual Case-Based Cooking

Fadi Badra
Rokia Bendaoud
  • Fonction : Auteur
  • PersonId : 830684
Julien Cojan
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  • PersonId : 836380
Thomas Meilender
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  • PersonId : 855192
Emmanuel Nauer
Amedeo Napoli
Yannick Toussaint
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  • PersonId : 832664

Résumé

This paper presents how the Taaable project addresses the textual case-based reasoning challenge of the CCC, thanks to a combination of principles, methods, and technologies of various fields of knowledge-based system technologies, namely CBR, ontology engineering manual and semi-automatic), data and text-mining using textual resources of the Web, text annotation (used as an indexing technique), knowledge representation, and hierarchical classification. Indeed, to be able to reason on textual cases, indexing them by a formal representation language using a formal vocabulary has proven to be useful.
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Dates et versions

inria-00337666 , version 1 (07-11-2008)

Identifiants

  • HAL Id : inria-00337666 , version 1

Citer

Fadi Badra, Rokia Bendaoud, Rim Bentebibel, Pierre-Antoine Champin, Julien Cojan, et al.. TAAABLE: Text Mining, Ontology Engineering, and Hierarchical Classification for Textual Case-Based Cooking. 9th European Conference on Case-Based Reasoning - ECCBR 2008, Workshop Proceedings, Sep 2008, Trier, Germany. pp.219--228. ⟨inria-00337666⟩
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