Results 51 to 60 of about 3,357,090 (344)
Text Summarization using different Methods for Deep Learning [PDF]
BIO Web of ConferencesIn the current era of rapid information expansion, text summarization has become vital for comprehending textual material. Physically condensing large textual volumes is challenging for humans, especially considering the vast amount of text content ...
Shaker Fatima +3 more
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Summarization Model Using Multi-Task Learning Fused with Text Classification [PDF]
Jisuanji gongcheng, 2021 The text summary should include all the important information in the source text,but the summaries generated by traditional summarization models based on encoder-decoder architecture are not accurate.Based on the correlation between text classification ...
ZHOU Weixiao, LAN Wenfei
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Generic Text Summarization for Turkish [PDF]
The Computer Journal, 2009 In this paper, we propose a generic text summarization method that generates summaries of Turkish texts by ranking sentences according to their scores calculated using their surface level features and extracting the highest ranked ones from the original documents.
Kutlu, Mucahid +2 more
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Summarization of Text and Image Captioning in Information Retrieval Using Deep Learning Techniques
IEEE Access, 2022 Automated information retrieval and text summarization concept is a difficult process in natural language processing because of the infrequent structure and high complexity of the documents.
P. Mahalakshmi, N. Sabiyath Fatima
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Tibetan Short Text Summarization Based on Fusion of Different Basic Units Information [PDF]
Jisuanji gongchengTibetan text summary enables users to quickly and effectively understand the content of the text. However, the scarcity of public, multi-domain, and large-scale Tibetan summarization datasets hinders the further development of Tibetan text summarization ...
XIA Wuji, HUANG Heming, FAN Yonghong, Gengzangcuomao, FAN Yutao
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Abstractive Text Summarization Model with Coherence Reinforcement and No Ground Truth Dependency [PDF]
Jisuanji kexue yu tansuo, 2022 Automatic text summarization aims to compress a given document, which can efficiently reflect the main idea of the source document with a short summary.
CHEN Gongchi, RONG Huan, MA Tinghuai
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Mapping the Design Space of Human-AI Interaction in Text Summarization [PDF]
North American Chapter of the Association for Computational Linguistics, 2022 Automatic text summarization systems commonly involve humans for preparing data or evaluating model performance, yet, there lacks a systematic understanding of humans’ roles, experience, and needs when interacting with or being assisted by AI.
Ruijia Cheng +4 more
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Survey of Deep Learning Based Extractive Summarization [PDF]
Jisuanji kexue yu tansuoAutomatic text summarization (ATS) is a popular research direction in natural language processing, and its main implementation methods are divided into two categories: extractive and abstractive. Extractive summarization directly uses the text content in
TIAN Xuan, LI Jialiang, MENG Xiaohuan
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Chart-to-Text: A Large-Scale Benchmark for Chart Summarization [PDF]
Annual Meeting of the Association for Computational Linguistics, 2022 Charts are commonly used for exploring data and communicating insights. Generating natural language summaries from charts can be very helpful for people in inferring key insights that would otherwise require a lot of cognitive and perceptual efforts.
Shankar Kanthara +6 more
semanticscholar +1 more source
A literature review of abstractive summarization methods
Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï, 2019 The paper contains a literature review for automatic abstractive text summarization. The classification of abstractive text summarization methods was considered.
D. V. Shypik, Petro I. Bidyuk
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