Extractive summarization of scientific publications (CROSBI ID 428878)
Ocjenski rad | diplomski rad
Podaci o odgovornosti
Krušić, Lucija
Martinčić-Ipšić, Sanda
engleski
Extractive summarization of scientific publications
This Master’s thesis aims to provide a comprehensive survey of state-of-the art methods used for the task of Automatic Text Summarization. Automatically made summaries can provide great benefits to everyday internet users and enhance the way we search for relevant and necessary information and save time and resources invested in human-made summaries. This thesis provides an overview of the field of ATS and covers the approaches to summarization, the real-world applications of summarization and the various evaluation metrics used to establish the quality of the generated summary. Automatic text summarization is a blooming field which has recently gained significant interest and presently, much advancement is being achieved with the use of neural networks. The thesis will provide a comprehensive survey of the recent work done in the field, including the datasets used and the state-of-the art results of recent studies. The various methods of approaching ATS are described in depth and compared on the basis of their effectiveness.
automatic text summarization, extractive summarization, abstractive summarization, natural language processing, deep neural networks
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Podaci o izdanju
125
16.09.2019.
obranjeno
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