Taxonomy Enrichment with Text and Graph Vector Representation
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-16500-9_2
Reference21 articles.
1. Arefyev, N., Fedoseev, M., Kabanov, A., Zizov, V.: Word2vec not dead: predicting hypernyms of co-hyponyms is better than reading definitions. In: Computational Linguistics and Intellectual Technologies: Papers from the Annual conference “Dialogue” (2020)
2. Bojanowski, P., Grave, E., Joulin, A., Mikolov, T.: Enriching word vectors with subword information. Trans. Assoc. Comput. Linguist. 5, 135–146 (2017)
3. Camacho-Collados, J., et al.: SemEval-2018 task 9: hypernym discovery. In: Proceedings of The 12th International Workshop on Semantic Evaluation, pp. 712–724. Association for Computational Linguistics, New Orleans, Louisiana (2018). www.aclweb.org/anthology/S18-1115, https://doi.org/10.18653/v1/S18-1115
4. Dale, D.: A simple solution for the taxonomy enrichment task: discovering hypernyms using nearest neighbor search. In: Computational Linguistics and Intellectual Technologies: Papers from the Annual Conference “Dialogue” (2020)
5. Espinosa-Anke, L., Ronzano, F., Saggion, H.: TALN at SemEval-2016 task 14: semantic taxonomy enrichment via sense-based embeddings. In: Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), pp. 1332–1336. Association for Computational Linguistics, San Diego, California (2016). www.aclweb.org/anthology/S16-1208, https://doi.org/10.18653/v1/S16-1208
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