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.
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Latiri, C., Ghezaiel, L.B., Ahmed, M.B. (2012). Proxemic Conceptual Network Based on Ontology Enrichment for Representing Documents in IR. In: ten Teije, A., et al. Knowledge Engineering and Knowledge Management. EKAW 2012. Lecture Notes in Computer Science(), vol 7603. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33876-2_9
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DOI: https://doi.org/10.1007/978-3-642-33876-2_9
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