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Hybridization of an Index Based on Concept Lattice with a Terminology Extraction Model for Semantic Information Retrieval Guided by WordNet

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Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) (HIS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 552))

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Abstract

In this paper, we present IRAFCA-WN an information retrieval system from textual documents. Our model includes an automatic extraction module of terminology and a module based on formal concept analysis (FCA) guided by WordNet for indexing. The experimental study on a standard test data shows the effectiveness of our hybrid model.

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Notes

  1. 1.

    https://wordnet.princeton.edu/wordnet/download/.

  2. 2.

    http://sourceforge.net/projects/conexp/.

  3. 3.

    http://ir.dcs.gla.ac.uk/resources/test_collections/medl/.

  4. 4.

    http://www.ims.uni-stuttgart.de/projekte/corplex/TreeTagger/.

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Fkih, F., Omri, M.N. (2017). Hybridization of an Index Based on Concept Lattice with a Terminology Extraction Model for Semantic Information Retrieval Guided by WordNet. In: Abraham, A., Haqiq, A., Alimi, A., Mezzour, G., Rokbani, N., Muda, A. (eds) Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016). HIS 2016. Advances in Intelligent Systems and Computing, vol 552. Springer, Cham. https://doi.org/10.1007/978-3-319-52941-7_15

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  • DOI: https://doi.org/10.1007/978-3-319-52941-7_15

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