QUESTION ANSWERING SYSTEM UPON UNIFIED LANGUAGE MODEL AND EVALUATING PERFORMANCE OF DATASETS
| dc.contributor.author | Ismagulov N. | |
| dc.date.accessioned | 2024-01-04T10:45:49Z | |
| dc.date.available | 2024-01-04T10:45:49Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Abstract. Present days require automation and optimization in simple but urgent tasks. It is granted to use opportunities of technologies and science in order to work efficiently and to stay productive. In this paper, I seek to understand opportunities and drawbacks of the publicly available datasets, such as SQuAD, TriviaQA, Natural Questions (NQ). QUAC, NewsQA. It is vital to choose a suitable dataset in order to create a system with better performance. Specifically, the paper proposes an automatic question creating system that uses state-of-the-art Natural Language Processing (NLP) - Unified Language Model (UniLM). The question generating algorithm was verified using best datasets, and it has shown noteworthy results - questions generated were logical and correct. This study is important for teachers, teacher assistants, to save time writing test questions and spend it for more important duties. | |
| dc.identifier.citation | N. Ismagulov / QUESTION ANSWERING SYSTEM UPON UNIFIED LANGUAGE MODEL AND EVALUATING PERFORMANCE OF DATASETS / СДУ хабаршысы - 2023 | |
| dc.identifier.issn | 2709-2631 | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1095 | |
| dc.language.iso | en | |
| dc.publisher | СДУ хабаршысы - 2023 | |
| dc.subject | NLP | |
| dc.subject | SQuAD | |
| dc.subject | dataset | |
| dc.subject | UniLM | |
| dc.subject | education | |
| dc.subject | wikipedia | |
| dc.subject | СДУ хабаршысы - 2023 | |
| dc.subject | №1 | |
| dc.title | QUESTION ANSWERING SYSTEM UPON UNIFIED LANGUAGE MODEL AND EVALUATING PERFORMANCE OF DATASETS | |
| dc.type | Article |