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An adaptive search mechanism with convolutional learning networks for online social media text summarization and classification model [PDF]
Scientific ReportsThe fast development of social media platforms has led to an unprecedented growth of daily short text content. Removing valued patterns and insights from this vast amount of textual data requires advanced methods to provide information while preserving ...
Reema G. AL-anazi +7 more
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Digithum, 2001 The coming of the WWW and of the Internet as a telecommunications network has changed the concept of what is considered information: the person who is best informed is not the one with the most information but the one with the best means for obtaining ...
Salvador Climent Roca
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SATS: simplification aware text summarization of scientific documents [PDF]
Frontiers in Artificial IntelligenceSimplifying summaries of scholarly publications has been a popular method for conveying scientific discoveries to a broader audience. While text summarization aims to shorten long documents, simplification seeks to reduce the complexity of a document. To
Farooq Zaman +5 more
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Empowering legal justice with AI: A reinforcement learning SAC-VAE framework for advanced legal text summarization. [PDF]
PLoS ONEAutomated summarization of legal texts poses a significant challenge due to the complex and specialized nature of legal documentation. Despite the recent progress in reinforcement learning for natural language text summarization, its application in the ...
Xukang Wang, Ying Cheng Wu
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Exploring the Limits of ChatGPT for Query or Aspect-based Text Summarization [PDF]
arXiv.org, 2023 Text summarization has been a crucial problem in natural language processing (NLP) for several decades. It aims to condense lengthy documents into shorter versions while retaining the most critical information. Various methods have been proposed for text
Xianjun Yang +4 more
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Segmented Summarization Model for Legal Documents [PDF]
Jisuanji gongcheng, 2022 Text summary refers to the process of summarization the content of text information, extracting the relevant content, and then formulating a summarization.Existing text summarization models usually analyze content selection and summarization generation ...
WANG Gang, SUN Yuanyuan, CHEN Yanguang, LIN Hongfei
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SummIt: Iterative Text Summarization via ChatGPT [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 Text summarization systems have made significant progress in recent years, but typically generate summaries in one single step. However, the one-shot summarization setting is sometimes inadequate, as the generated summary may contain hallucinations or ...
Haopeng Zhang, Xiao Liu, Jiawei Zhang
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Journal of ICT, 2021 Text summarization aims to reduce text by removing less useful information to obtain information quickly and precisely. In Indonesian abstractive text summarization, the research mostly focuses on multi-document summarization which methods will not work ...
Henry Lucky, Derwin Suhartono
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Natural Language Processing For Automatic text summarization [Datasets] - Survey
Wasit Journal of Computer and Mathematics Science, 2022 Natural language processing has developed significantly recently, which has progressed the text summarization task. It is no longer limited to reducing the text size or obtaining helpful information from a long document only.
Alaa Ahmed AL-Banna +1 more
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Text Summarization with Pretrained Encoders [PDF]
Conference on Empirical Methods in Natural Language Processing, 2019 Bidirectional Encoder Representations from Transformers (BERT) represents the latest incarnation of pretrained language models which have recently advanced a wide range of natural language processing tasks.
Yang Liu, Mirella Lapata
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