Attentional Extractive Summarization
Applied Sciences, 2023 In this work, a general theoretical framework for extractive summarization is proposed—the Attentional Extractive Summarization framework. Although abstractive approaches are generally used in text summarization today, extractive methods can be ...
José Ángel González +4 more
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A study of extractive summarization of long documents incorporating local topic and hierarchical information [PDF]
Scientific ReportsIn recent years, the transformer-based language models have achieved remarkable success in the field of extractive text summarization. However, there are still some limitations in this kind of research.
Ting Wang +7 more
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Constrained quantum optimization for extractive summarization on a trapped-ion quantum computer. [PDF]
Sci Rep, 2022 Realizing the potential of near-term quantum computers to solve industry-relevant constrained-optimization problems is a promising path to quantum advantage.
Niroula P +6 more
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GRETEL: Graph Contrastive Topic Enhanced Language Model for Long Document Extractive Summarization [PDF]
International Conference on Computational Linguistics, 2022 Recently, neural topic models (NTMs) have been incorporated into pre-trained language models (PLMs), to capture the global semantic information for text summarization.
Qianqian Xie +3 more
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Exploring optimal granularity for extractive summarization of unstructured health records: Analysis of the largest multi-institutional archive of health records in Japan [PDF]
PLOS Digital Health, 2022 Automated summarization of clinical texts can reduce the burden of medical professionals. “Discharge summaries” are one promising application of the summarization, because they can be generated from daily inpatient records.
Kenichiro Ando +4 more
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DiffuSum: Generation Enhanced Extractive Summarization with Diffusion [PDF]
Annual Meeting of the Association for Computational Linguistics, 2023 Extractive summarization aims to form a summary by directly extracting sentences from the source document. Existing works mostly formulate it as a sequence labeling problem by making individual sentence label predictions.
Haopeng Zhang, Xiao Liu, Jiawei Zhang
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SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents [PDF]
AAAI Conference on Artificial Intelligence, 2016 We present SummaRuNNer, a Recurrent Neural Network (RNN) based sequence model for extractive summarization of documents and show that it achieves performance better than or comparable to state-of-the-art.
Ramesh Nallapati +2 more
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Text summarization method of argumentative discourse by combining the BERT-transformer model [PDF]
Frontiers in Artificial IntelligenceSummarization of texts have been considered as essential practice nowadays with the careful presentation of the main ideas of a text. The current study aims to provide a methodology of summarizing complex texts such as argumentative discourse. Extractive
Yaser Altameemi +4 more
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A novel centroid based sentence classification approach for extractive summarization of COVID-19 news reports. [PDF]
Int J Inf Technol, 2023 Banerjee S +2 more
europepmc +3 more sources
Extractive Summarization of Call Transcripts [PDF]
IEEE Access, 2022 Automatic text summarization is one of the most challenging and interesting problems in natural language processing (NLP). Text summarization is the process of extracting the most important information from the text and presenting it concisely in fewer ...
Pratik K. Biswas, Aleksandr Iakubovich
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