Results 31 to 40 of about 4,298,648 (328)
EntSUM: A Data Set for Entity-Centric Extractive Summarization [PDF]
Annual Meeting of the Association for Computational Linguistics, 2022 Controllable summarization aims to provide summaries that take into account user-specified aspects and preferences to better assist them with their information need, as opposed to the standard summarization setup which build a single generic summary of a
Mounica Maddela +2 more
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Extractive summarization of meeting recordings [PDF]
Interspeech 2005, 2005 Several approaches to automatic speech summarization are discussed below, using the ICSI Meetings corpus. We contrast feature-based approaches using prosodic and lexical features with maximal marginal relevance and latent semantic analysis approaches to summarization.
Murray, Gabriel +2 more
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Neural Attention Model for Abstractive Text Summarization Using Linguistic Feature Space
IEEE Access, 2023 Summarization generates a brief and concise summary which portrays the main idea of the source text. There are two forms of summarization: abstractive and extractive.
Aniqa Dilawari +4 more
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Systematic TextRank Optimization in Extractive Summarization
Recent Advances in Natural Language Processing, 2023 With the ever-growing amount of textual data, extractive summarization has become increasingly crucial for efficiently processing information. The TextRank algorithm, a popular unsupervised method, offers excellent potential for this task. In this paper,
Morris Zieve +5 more
semanticscholar +1 more source
Performance Study on Extractive Text Summarization Using BERT Models
Information, 2022 The task of summarization can be categorized into two methods, extractive and abstractive. Extractive summarization selects the salient sentences from the original document to form a summary while abstractive summarization interprets the original ...
Shehab Abdel-Salam, Ahmed Rafea
doaj +1 more source
Revisiting Automatic Evaluation of Extractive Summarization Task: Can We Do Better than ROUGE?
Findings, 2022 It has been the norm for a long time to evaluate automated summarization tasks using the popular ROUGE metric. Although several studies in the past have highlighted the limitations of ROUGE, researchers have struggled to reach a consensus on a better ...
Mousumi Akter +2 more
semanticscholar +1 more source
The Design of Automatic Summarization of Indonesian Texts Using a Hybrid Approach
Jurnal Teknologi Informasi dan Pendidikan, 2022 This study aims to design a model for automatic text summarization in Indonesian. Automatic text summarization is a system that reduces the number of sentences without losing important information in the document.
Kania Evita Dewi +1 more
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Ranking Sentences for Extractive Summarization with Reinforcement Learning [PDF]
North American Chapter of the Association for Computational Linguistics, 2018 Single document summarization is the task of producing a shorter version of a document while preserving its principal information content. In this paper we conceptualize extractive summarization as a sentence ranking task and propose a novel training ...
Shashi Narayan +2 more
semanticscholar +1 more source
Summarizing Scientific Texts: Experiments with Extractive Summarizers [PDF]
Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007), 2007 In this paper we present experiments on scientific text summarization. From a complete text, we produce a shorter version containing all the main parts of the research. Having in mind the sophisticated structure of such texts, we show that good results can be achieved using simple extractive summarizers with some obvious improvements that consider the ...
Pedro Paulo Balage Filho +1 more
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Improving Unsupervised Extractive Summarization with Facet-Aware Modeling
Findings, 2021 Unsupervised extractive summarization aims to extract salient sentences from documents without labeled corpus. Existing methods are mostly graph-based by computing sentence centrality. These methods usually tend to select sentences within the same facet,
Xinnian Liang +3 more
semanticscholar +1 more source