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NLP TRANSFORMERS: ANALYSIS OF LLMS AND TRADITIONAL APPROACHES FOR ENHANCED TEXT SUMMARIZATION
- Source :
- Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi, Vol 32, Iss 1, Pp 1140-1151 (2024)
- Publication Year :
- 2024
- Publisher :
- Eskişehir Osmangazi University, 2024.
-
Abstract
- As the amount of the available information continues to grow, finding the relevant information has become increasingly challenging. As a solution, text summarization has emerged as a vital method for extracting essential information from lengthy documents. There are various techniques available for filtering documents and extracting the pertinent information. In this study, a comparative analysis is conducted to evaluate traditional approaches and state-of-the-art methods on the BBC News and CNN/DailyMail datasets. This study offers valuable insights for researchers to advance their research and helps practitioners in selecting the most suitable techniques for their specific use cases.
Details
- Language :
- English, Turkish
- ISSN :
- 26305712
- Volume :
- 32
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9f2bb7d606343df8471dba5c44d3485
- Document Type :
- article
- Full Text :
- https://doi.org/10.31796/ogummf.1303569