Abstract
In this paper, we present our method of lexical enrichment applied on a semantic network in the context of query disambiguation. This network represents the list of relevant sentences in French (noted by listRSF) that respond to a given Arabic query. In a first step we generate the semantic network covering the content of the listRSF. The generation of the network is based on our approach of semantic and conceptual indexing. In a second step, we apply a contextual enrichment on this network using association rules model. The evaluation of our method shows the impact of this model on the semantic network enrichment. As a result, this enrichment increases the F-measure from 71% to 81% in terms of the (listeRSF) coverage.
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Mallat, S., Hkiri, E., Maraoui, M., Zrigui, M. (2015). Lexical Network Enrichment Using Association Rules Model. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science(), vol 9041. Springer, Cham. https://doi.org/10.1007/978-3-319-18111-0_5
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DOI: https://doi.org/10.1007/978-3-319-18111-0_5
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