TAAABLE: Text Mining, Ontology Engineering, and Hierarchical Classification for Textual Case-Based Cooking - Archive ouverte HAL Access content directly
Conference Papers Year : 2008

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

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

Abstract

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 and versions

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

Identifiers

  • HAL Id : inria-00337666 , version 1

Cite

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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