Ontology-based approach for measuring semantic similarity

Author:

Hadj Taieb Mohamed Ali,Ben Aouicha Mohamed,Ben Hamadou Abdelmajid

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference60 articles.

1. Agirre, E., Alfonseca, E., Hall, K., Kravalova, J., Pasca, M., Soroa, A., 2009. A study on similarity and relatedness using distributional and WordNet-based approaches. In: Proceedings of the Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, NAACL׳09, Association for Computational Linguistics, Stroudsburg, PA, USA, pp. 19–27.

2. Al-Mubaid, H., Nguyen, H.A., 2006. A cluster-based approach for semantic similarity in the biomedical domain. In: Proceedings of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2006. IEEE Computer Society, New York, USA, pp. 2713–2717.

3. Discovering implicit intention-level knowledge from natural-language texts;Atkinson;Knowl.-based Syst.,2009

4. Banerjee, S., Pedersen, T., 2003. Extended gloss overlaps as a measure of semantic relatedness. In: Proceedings of the 18th International Joint Conference on Artificial Intelligence (San Francisco, CA, USA), IJCAI׳03, Morgan Kaufmann Publishers Inc., pp. 805–810.

5. Budanitsky, A., Hirst, G., 2001. Semantic distance in WordNet: an experimental, application-oriented evaluation of five measures. Workshop on WordNet and Other Lexical Resources, Second meeting of the North American Chapter of the Association for Computational Linguistics, Pittsburgh, USA.

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