Results 11 to 20 of about 4,298,648 (328)
Learning-Free Unsupervised Extractive Summarization Model
IEEE Access, 2021 Text summarization is an information condensation technique that abbreviates a source document to a few representative sentences with the intention to create a coherent summary containing relevant information of source corpora. This promising subject has
Myeongjun Jang, Pilsung Kang
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Unified extractive-abstractive summarization: a hybrid approach utilizing BERT and transformer models for enhanced document summarization [PDF]
PeerJ Computer ScienceWith the exponential proliferation of digital documents, there arises a pressing need for automated document summarization (ADS). Summarization, a compression technique, condenses a source document into concise sentences that encapsulate its salient ...
Divya S. +3 more
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Applied SciencesExtractive summarization, a pivotal task in natural language processing, aims to distill essential content from lengthy documents efficiently. Traditional methods often struggle with capturing the nuanced interdependencies between different document ...
Aytuğ Onan, Hesham Alhumyani
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SciBERTSUM: Extractive Summarization for Scientific Documents
International Workshop on Document Analysis Systems, 2022 The summarization literature focuses on the summarization of news articles. The news articles in the CNN-DailyMail are relatively short documents with about 30 sentences per document on average. We introduce SciBERTSUM, our summarization framework designed for the summarization of long documents like scientific papers with more than 500 sentences ...
Sefid, Athar, Giles, C Lee
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Efficient GAN-based Method for Extractive Summarization [PDF]
Journal of Electrical and Computer Engineering Innovations, 2022 Background and Objectives: Text summarization plays an essential role in reducing time and cost in many domains such as medicine, engineering, etc. On the other hand, manual summarization requires much time.
S.V. Moravvej +3 more
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Deep learning-based methodology for vulnerability detection in smart contracts [PDF]
PeerJ Computer ScienceSmart contracts play an essential role in the handling and management of digital assets, where vulnerabilities can lead to severe security issues and financial losses. Current detection techniques are largely limited to identifying single vulnerabilities
Zhibo Wang +5 more
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Extractive Summarization via ChatGPT for Faithful Summary Generation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 Extractive summarization is a crucial task in natural language processing that aims to condense long documents into shorter versions by directly extracting sentences.
Haopeng Zhang, Xiao Liu, Jiawei Zhang
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Abstractive text summarization of low-resourced languages using deep learning [PDF]
PeerJ Computer Science, 2023 Background Humans must be able to cope with the huge amounts of information produced by the information technology revolution. As a result, automatic text summarization is being employed in a range of industries to assist individuals in identifying the ...
Nida Shafiq +5 more
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Legal Extractive Summarization of U.S. Court Opinions [PDF]
LIRAI@HT, 2023 This paper tackles the task of legal extractive summarization using a dataset of 430K U.S. court opinions with key passages annotated. According to automated summary quality metrics, the reinforcement-learning-based MemSum model is best and even out ...
Emmanuel J. Bauer +3 more
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Extractive Summarization as Text Matching [PDF]
Annual Meeting of the Association for Computational Linguistics, 2020 This paper creates a paradigm shift with regard to the way we build neural extractive summarization systems. Instead of following the commonly used framework of extracting sentences individually and modeling the relationship between sentences, we ...
Ming Zhong +5 more
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