Genetic Based Optimization Models for Enhancing Multi- Document Text Summarization [PDF]
Engineering and Technology Journal, 2015 Extractive multi-document text summarization – a summarization with the aim of removing redundant information in a document collectionwhile preserving its salient sentences – has recently enjoyed a large interest in proposing automatic models.This paper ...
Hilal H. Saleh, Nasreen J. Kadhim
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Multi-document summarization by sentence extraction [PDF]
NAACL-ANLP 2000 Workshop on Automatic Summarization -, 2000 This paper discusses a text extraction approach to multi-document summarization that builds on single-document summarization methods by using additional, available information about the document set as a whole and the relationships between the documents.
Goldstein, Jade +3 more
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Hierarchical Summarization: Scaling Up Multi-Document Summarization [PDF]
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2014 Multi-document summarization (MDS) systems have been designed for short, unstructured summaries of 10-15 documents, and are inadequate for larger document collections. We propose a new approach to scaling up summarization called hierarchical summarization, and present the first implemented system, SUMMA.
Janara Christensen +3 more
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Extractive multi-document text summarization based on graph independent sets
Egyptian Informatics Journal, 2020 We propose a novel methodology for extractive, generic summarization of text documents. The Maximum Independent Set, which has not been used previously in any summarization study, has been utilized within the context of this study.
Taner Uçkan, Ali Karcı
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An evolutionary framework for multi document summarization using Cuckoo search approach: MDSCSA
Applied Computing and Informatics, 2018 In today's scenario the rate of growth of information is expanding exponentially in the World Wide Web. As a result, extracting valid and useful information from a huge data has become a challenging issue. Recently text summarization is recognized as one
Rasmita Rautray +1 more
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occams: A Text Summarization Package
Analytics, 2023 Extractive text summarization selects asmall subset of sentences from a document, which gives good “coverage” of a document. When given a set of term weights indicating the importance of the terms, the concept of coverage may be formalized into a ...
Clinton T. White +3 more
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Integrating particle swarm optimization with backtracking search optimization feature extraction with two-dimensional convolutional neural network and attention-based stacked bidirectional long short-term memory classifier for effective single and multi-document summarization [PDF]
PeerJ Computer ScienceThe internet now offers a vast amount of information, which makes finding relevant data quite challenging. Text summarization has become a prominent and effective method towards glean important information from numerous documents.
Jyotirmayee Rautaray +2 more
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Fine-Grained Multi-Document Summarization Extraction Based on Heterogeneous Graph Hierarchical Learning [PDF]
Jisuanji gongchengThe objective of multi-document summarization extraction is to extract common key information from multi-documents. Multi-document summarization extraction requires higher simplicity than single-document summarization extraction.
Yuyuan WENG, Boyan XU, Ruichu CAI
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MSˆ2: Multi-Document Summarization of Medical Studies [PDF]
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021 To assess the effectiveness of any medical intervention, researchers must conduct a time-intensive and highly manual literature review. NLP systems can help to automate or assist in parts of this expensive process. In support of this goal, we release MS^2 (Multi-Document Summarization of Medical Studies), a dataset of over 470k documents and 20k ...
DeYoung, Jay +4 more
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Multi-document extractive text summarization based on firefly algorithm
Journal of King Saud University: Computer and Information Sciences, 2022 Extracting relevant information from a large amount of data is a challenging task. Automatic text summarization is a potential solution for obtaining this information. In this paper, a nature inspired swarm intelligence-based algorithm viz.
Minakshi Tomer, Manoj Kumar
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