Results 21 to 30 of about 4,298,648 (328)
Extractive is not Faithful: An Investigation of Broad Unfaithfulness Problems in Extractive Summarization [PDF]
Annual Meeting of the Association for Computational Linguistics, 2022 The problems of unfaithful summaries have been widely discussed under the context of abstractive summarization. Though extractive summarization is less prone to the common unfaithfulness issues of abstractive summaries, does that mean extractive is equal
Shiyue Zhang, David Wan, Mohit Bansal
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Extractive social media text summarization based on MFMMR-BertSum
Array, 2023 The advancement of computer technology has led to an overwhelming amount of textual information, hindering the efficiency of knowledge intake. To address this issue, various text summarization techniques have been developed, including statistics, graph ...
Junqing Fan +5 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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International Journal of Advanced Research in Science, Communication and Technology, 2022 In this fast paced technological era, where huge quantity of information is generating on the internet day by day. Since the dotcom bubble burst back in 2000, technology has radically transformed our societies. So, it is necessary to provide the better mechanism to extract the useful information fast and most effectively.
null Vivek S. Bhore +4 more
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Incorporating domain knowledge for extractive summarization of legal case documents [PDF]
International Conference on Artificial Intelligence and Law, 2021 Automatic summarization of legal case documents is an important and practical challenge. Apart from many domain-independent text summarization algorithms that can be used for this purpose, several algorithms have been developed specifically for ...
Paheli Bhattacharya +4 more
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Unsupervised Extractive Summarization using Pointwise Mutual Information [PDF]
Conference of the European Chapter of the Association for Computational Linguistics, 2021 Unsupervised approaches to extractive summarization usually rely on a notion of sentence importance defined by the semantic similarity between a sentence and the document.
Vishakh Padmakumar, He He
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Abstractive vs. Extractive Summarization: An Experimental Review
Applied Sciences, 2023 Text summarization is a subtask of natural language processing referring to the automatic creation of a concise and fluent summary that captures the main ideas and topics from one or multiple documents.
Nikolaos Giarelis +2 more
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Scientific Paper Extractive Summarization Enhanced by Citation Graphs [PDF]
Conference on Empirical Methods in Natural Language Processing, 2022 In a citation graph, adjacent paper nodes share related scientific terms and topics. The graph thus conveys unique structure information of document-level relatedness that can be utilized in the paper summarization task, for exploring beyond the intra ...
Xiuying Chen +5 more
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Study on Extractive Summarization with Global Information [PDF]
Jisuanji kexue, 2023 Extractive automatic text summarization aims to extract the sentences that can best express the semantics of the full text from the original text to form a summary.It is widely used and studied due to its simplicity and efficiency.Currently,extractive ...
ZHANG Xiang, MAO Xingjing, ZHAO Rongmei, JU Shenggen
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AUTOMATED SUMMARIZATION OF RESTAURANT REVIEWS USING HYBRID APPROACHES
ICTACT Journal on Soft Computing, 2022 The arena of automatic text summarization incorporates the paramount and relevant information from a large document. This research paper attempts at representing two hybrid models for automatic text summarization.
Shini George, V. Srividhya
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