Morphosyntactic Evaluation for Text Summarization in Morphologically Rich Languages: A Case Study for Turkish

Author:

Baykara BatuhanORCID,Güngör TungaORCID

Publisher

Springer Nature Switzerland

Reference32 articles.

1. Akın, A.A., Akın, M.D.: Zemberek, an open source NLP framework for Turkic languages. Structure 10, 1–5 (2007)

2. Altan, Z.: A Turkish automatic text summarization system. In: IASTED International Conference on (2004)

3. Banerjee, S., Lavie, A.: METEOR: an automatic metric for MT evaluation with improved correlation with human judgments. In: Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization, Ann Arbor, Michigan, pp. 65–72. Association for Computational Linguistics (2005)

4. Baykara, B., Güngör, T.: Abstractive text summarization and new large-scale datasets for agglutinative languages Turkish and Hungarian. Lang. Resour. Eval. 56, 1–35 (2022)

5. Baykara, B., Güngör, T.: Turkish abstractive text summarization using pretrained sequence-to-sequence models. Nat. Lang. Eng. 1–30 (2022)

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