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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5...13 Hits 1 – 20 of 244 1 Summarization datasets from the KAS corpus KAS-Sum 1.0 Žagar, Aleš; Kavaš, Matic; Robnik-Šikonja, Marko. - : Faculty of Electrical Engineering and Computer Science, University of Maribor, 2022. : Faculty of Computer and Information Science, University of Ljubljana, 2022 BASE Show details 2 A Novel Approach for Semantic Extractive Text Summarization Waseemullah Waseemullah; Zainab Fatima; Shehnila Zardari; Muhammad Fahim; Maria Andleeb Siddiqui; Ag. Asri Ag. Ibrahim; Kashif Nisar; Laviza Falak Naz In: Applied Sciences; Volume 12; Issue 9; Pages: 4479 (2022) Abstract: Text summarization is a technique for shortening down or exacting a long text or document. It becomes critical when someone needs a quick and accurate summary of very long content. Manual text summarization can be expensive and time-consuming. While summarizing, some important content, such as information, concepts, and features of the document, can be lost; therefore, the retention ratio, which contains informative sentences, is lost, and if more information is added, then lengthy texts can be produced, increasing the compression ratio. Therefore, there is a tradeoff between two ratios (compression and retention). The model preserves or collects all the informative sentences by taking only the long sentences and removing the short sentences with less of a compression ratio. It tries to balance the retention ratio by avoiding text redundancies and also filters irrelevant information from the text by removing outliers. It generates sentences in chronological order as the sentences are mentioned in the original document. It also uses a heuristic approach for selecting the best cluster or group, which contains more meaningful sentences that are present in the topmost sentences of the summary. Our proposed model extractive summarizer overcomes these deficiencies and tries to balance between compression and retention ratios. Keyword: semantic text extraction; text extraction; text mining; text summarization URL: https://doi.org/10.3390/app12094479 BASE Hide details 3 Two New Datasets for Italian-Language Abstractive Text Summarization Nicola Landro; Ignazio Gallo; Riccardo La Grassa; Edoardo Federici In: Information; Volume 13; Issue 5; Pages: 228 (2022) BASE Show details 4 Overview of SimpleText 2021 - CLEF Workshop on Text Simplification for Scientific Information Access Ermakova, Liana; Bellot, Patrice; Braslavski, Pavel... In: Experimental IR Meets Multilinguality, Multimodality, and Interaction: 12th International Conference of the CLEF Association, CLEF 2021, Virtual Event, September 21–24, 2021, Proceedings ; ISBN: 978-3-030-85251-1 ; 12th Conference and Labs of the Evaluation Forum (CLEF 2021) ; https://hal.archives-ouvertes.fr/hal-03637807 ; 12th Conference and Labs of the Evaluation Forum (CLEF 2021), Sep 2021, Bucharest, Romania. pp.432-449, ⟨10.1007/978-3-030-85251-1_27⟩ ; http://clef2021.clef-initiative.eu/ (2021) BASE Show details 5 Rewards with Negative Examples for Reinforced Topic-Focused Abstractive Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Markus; Liu, Can. - : Underline Science Inc., 2021 BASE Show details 6 Low-Resource Dialogue Summarization with Domain-Agnostic Multi-Source Pretraining ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Zou, Yicheng. - : Underline Science Inc., 2021 BASE Show details 7 HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; He, Lifang; LIU, YE. - : Underline Science Inc., 2021 BASE Show details 8 CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cao, Shuyang; Wang, Lu. - : Underline Science Inc., 2021 BASE Show details 9 Weakly supervised discourse segmentation for multiparty oral conversations ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ferrané, Isabelle; Gravellier, Lila. - : Underline Science Inc., 2021 BASE Show details 10 Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Dai, Wenliang; Fung, Pascale. - : Underline Science Inc., 2021 BASE Show details 11 Evaluation of Summarization Systems across Gender, Age, and Race ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Jørgensen, Anna; Søgaard, Anders. - : Underline Science Inc., 2021 BASE Show details 12 Controllable Neural Dialogue Summarization with Personal Named Entity Planning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chen, Nancy; Liu, Zhengyuan. - : Underline Science Inc., 2021 BASE Show details 13 CSDS: A Fine-Grained Chinese Dataset for Customer Service Dialogue Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Lin, Haitao; Ma, Liqun. - : Underline Science Inc., 2021 BASE Show details 14 A Thorough Evaluation of Task-Specific Pretraining for Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Maynez, Joshua; Narayan, Shashi. - : Underline Science Inc., 2021 BASE Show details 15 Effective Sequence-to-Sequence Dialogue State Tracking ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cao, Yuan; Mahdieh, Mahdis. - : Underline Science Inc., 2021 BASE Show details 16 Context or No Context? A preliminary exploration of human-in-the-loop approach for Incremental Temporal Summarization in meetings ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Saurav; Beckage, Nicole. - : Underline Science Inc., 2021 BASE Show details 17 Exploring Multitask Learning for Low-Resource Abstractive Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Elaraby, Mohamed; Litman, Diane. - : Underline Science Inc., 2021 BASE Show details 18 Capturing Speaker Incorrectness: Speaker-Focused Post-Correction for Abstractive Dialogue Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Lee, Dongyub. - : Underline Science Inc., 2021 BASE Show details 19 Narrative Embedding: Re-Contextualization Through Attention ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Glick, Madeleine; Wilner, Sean. - : Underline Science Inc., 2021 BASE Show details 20 TWEETSUMM - A Dialog Summarization Dataset for Customer Service ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Feigenblat, Guy; Gunasekara, Chulaka. - : Underline Science Inc., 2021 BASE Show details Page: 1 2 3 4 5...13

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