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

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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. © 2012 Springer-Verlag.

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APA

Latiri, C., Ghezaiel, L. B., & Ahmed, M. B. (2012). Proxemic conceptual network based on ontology enrichment for representing documents in IR. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7603 LNAI, pp. 72–86). https://doi.org/10.1007/978-3-642-33876-2_9

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