Results 1 to 10 of about 234 (196)
Do Multi-Document Summarization Models Synthesize?
Transactions of the Association for Computational LinguisticsAbstract Multi-document summarization entails producing concise synopses of collections of inputs. For some applications, the synopsis should accurately synthesize inputs with respect to a key aspect, e.g., a synopsis of film reviews written about a particular movie should reflect the average critic consensus.
Jay DeYoung +3 more
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Text Summarization in Multi Document Using Genetic Algorithm
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2021 Automatic text summarization is a representation of a document that contains the essence or main focus of the document. Text summarization is automatically performed using the extraction method.
Nirwana Hendrastuty, Azhari SN
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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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A survey for multi-document summarization [PDF]
Proceedings of the HLT-NAACL 03 on Text summarization workshop -, 2003 Automatic Multi-Document summarization is still hard to realize. Under such circumstances, we believe, it is important to observe how humans are doing the same task, and look around for different strategies.We prepared 100 document sets similar to the ones used in the DUC multi-document summarization task. For each document set, several people prepared
Sekine, Satoshi, Nobata, Chikashi
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A Framework for Generating Extractive Summary from Multiple Malayalam Documents
Information, 2021 Automatic extractive text summarization retrieves a subset of data that represents most notable sentences in the entire document. In the era of digital explosion, which is mostly unstructured textual data, there is a demand for users to understand the ...
K. Manju +2 more
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Multi-Document Summarization: A Comparative Evaluation
2023 IEEE 17th International Conference on Industrial and Information Systems (ICIIS), 2023 This paper is aimed at evaluating state-of-the-art models for Multi-document Summarization (MDS) on different types of datasets in various domains and investigating the limitations of existing models to determine future research directions. To address this gap, we conducted an extensive literature review to identify state-of-the-art models and datasets.
Hewapathirana, Kushan +2 more
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Template-Based Headline Generator for Multiple Documents
IEEE Access, 2022 In this paper, we develop a neural multi-document summarization model, named MuD2H (refers to Multi-Document to Headline) to generate an attractive and customized headline from a set of product descriptions.
Yun-Chien Tseng +4 more
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How “Multi” is Multi-Document Summarization?
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022 The task of multi-document summarization (MDS) aims at models that, given multiple documents as input, are able to generate a summary that combines disperse information, originally spread across these documents. Accordingly, it is expected that both reference summaries in MDS datasets, as well as system summaries, would indeed be based on such ...
Wolhandler, Ruben +3 more
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Journal of Hebei University of Science and Technology, 2020 In order to solve the problem of ineffective utilization of the semantic information between documents in the traditional multi-document extractive summarization method and the excessive redundant content in the summary result, a Khmer multi-document ...
Zhaolin ZENG +4 more
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Mathematics, 2023 In the area of text summarization, there have been significant advances recently. In the meantime, the current trend in text summarization is focused more on news summarization. Therefore, developing a synthesis approach capable of extracting, comparing,
Chandrakala Arya +5 more
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