Показати скорочений опис матеріалу
dc.contributor.author | Yarish, Dzvenymyra![]() |
|
dc.date.accessioned | 2024-02-14T16:24:25Z | |
dc.date.available | 2024-02-14T16:24:25Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Yarish, Dzvenymyra. Sentence Simplification in context of Automatic Question Generation / Yarish, Dzvenymyra; Supervisor: Jan Sedivy; Ukrainian Catholic University, Department of Computer Sciences. – Lviv: 2019. – 36 p. | uk |
dc.identifier.uri | https://er.ucu.edu.ua/handle/1/4483 | |
dc.language.iso | en | uk |
dc.title | Sentence Simplification in context of Automatic Question Generation | uk |
dc.type | Preprint | uk |
dc.status | Публікується вперше | uk |
dc.description.abstracten | Automatic question generation is a promising field of research. Sentence simplifi- cation is a key to the high-quality question generation. In this work we explore the existing sentence simplification approaches, present an valuable extension to the ex- isting sentence simplification datasets and experiment with the latest seq2seq tech- niques. Our model makes use of transfer learning, which to our knowledge, is the first attempt to apply that method to sentence simplification. We evaluate our model against the rule - based approach and a baseline machine learning model and see im- provements in the paraphrasing component of sentence simplification. | uk |