Proxemic conceptual network based on ontology enrichment for representing documents in IR

  • Authors:
  • Chiraz Latiri;Lamia Ben Ghezaiel;Mohamed Ben Ahmed

  • Affiliations:
  • LIPAH Research Laboratory, Computer Sciences Department, Faculty of Sciences of Tunis, El Manar University, Tunis, Tunisia;Computer Sciences School Riadi-Gdl Research Laboratory, Manouba University, Tunis, Tunisia;Computer Sciences School Riadi-Gdl Research Laboratory, Manouba University, Tunis, Tunisia

  • Venue:
  • EKAW'12 Proceedings of the 18th international conference on Knowledge Engineering and Knowledge Management
  • Year:
  • 2012

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Abstract

In this paper, we propose the use of a minimal generic basis of association rules (ARs) between terms, in order to automatically enrich an existing domain ontology. The final result is a proxemic conceptual network which contains additional implicit knowledge. Therefore, to evaluate our ontology enrichment approach, we propose a novel document indexing approach based on this proxemic network. The experiments carried out on the OHSUMED document collection of the TREC 9 filtring track and MeSH ontology showed that our conceptual indexing approach could considerably enhance information retrieval effectiveness.