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Статті в журналах з теми "Extractive Question-Answering"
Xu, Marie-Anne, and Rahul Khanna. "Evaluation of Single-Span Models on Extractive Multi-Span Question-Answering." International journal of Web & Semantic Technology 12, no. 1 (January 31, 2021): 19–29. http://dx.doi.org/10.5121/ijwest.2021.12102.
Повний текст джерелаGuan, Yue, Zhengyi Li, Zhouhan Lin, Yuhao Zhu, Jingwen Leng, and Minyi Guo. "Block-Skim: Efficient Question Answering for Transformer." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 10 (June 28, 2022): 10710–19. http://dx.doi.org/10.1609/aaai.v36i10.21316.
Повний текст джерелаHu, Zhongjian, Peng Yang, Bing Li, Yuankang Sun, and Biao Yang. "Biomedical extractive question answering based on dynamic routing and answer voting." Information Processing & Management 60, no. 4 (July 2023): 103367. http://dx.doi.org/10.1016/j.ipm.2023.103367.
Повний текст джерелаOuyang, Jianquan, and Mengen Fu. "Improving Machine Reading Comprehension with Multi-Task Learning and Self-Training." Mathematics 10, no. 3 (January 19, 2022): 310. http://dx.doi.org/10.3390/math10030310.
Повний текст джерелаShinoda, Kazutoshi, Saku Sugawara, and Akiko Aizawa. "Which Shortcut Solution Do Question Answering Models Prefer to Learn?" Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 11 (June 26, 2023): 13564–72. http://dx.doi.org/10.1609/aaai.v37i11.26590.
Повний текст джерелаLongpre, Shayne, Yi Lu, and Joachim Daiber. "MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answering." Transactions of the Association for Computational Linguistics 9 (2021): 1389–406. http://dx.doi.org/10.1162/tacl_a_00433.
Повний текст джерелаGholami, Sia, and Mehdi Noori. "You Don’t Need Labeled Data for Open-Book Question Answering." Applied Sciences 12, no. 1 (December 23, 2021): 111. http://dx.doi.org/10.3390/app12010111.
Повний текст джерелаLI, SHASHA, and ZHOUJUN LI. "QUESTION-ORIENTED ANSWER SUMMARIZATION VIA TERM HIERARCHICAL STRUCTURE." International Journal of Software Engineering and Knowledge Engineering 21, no. 06 (September 2011): 877–89. http://dx.doi.org/10.1142/s0218194011005475.
Повний текст джерелаMoon, Sungrim, Huan He, Heling Jia, Hongfang Liu, and Jungwei Wilfred Fan. "Extractive Clinical Question-Answering With Multianswer and Multifocus Questions: Data Set Development and Evaluation Study." JMIR AI 2 (June 20, 2023): e41818. http://dx.doi.org/10.2196/41818.
Повний текст джерелаSiblini, Wissam, Mohamed Challal, and Charlotte Pasqual. "Efficient Open Domain Question Answering With Delayed Attention in Transformer-Based Models." International Journal of Data Warehousing and Mining 18, no. 2 (April 2022): 1–16. http://dx.doi.org/10.4018/ijdwm.298005.
Повний текст джерелаДисертації з теми "Extractive Question-Answering"
Bergkvist, Alexander, Nils Hedberg, Sebastian Rollino, and Markus Sagen. "Surmize: An Online NLP System for Close-Domain Question-Answering and Summarization." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-412247.
Повний текст джерелаMängden data som är tillgänglig och konsumeras av människor växer globalt. För att minska den mentala trötthet och öka den allmänna förmågan att få insikt i komplexa, massiva texter eller dokument, har vi utvecklat en applikation för att bistå i de uppgifterna. Applikationen tillåter användare att ladda upp dokument och fråga kontextspecifika frågor via vår webbapplikation. En sammanfattad version av varje dokument presenteras till användaren, vilket kan ytterligare förenkla förståelsen av ett dokument och vägleda dem mot vad som kan vara relevanta frågor att ställa. Vår applikation ger användare möjligheten att behandla olika typer av dokument, är tillgänglig för alla, sparar ingen personlig data, och använder de senaste modellerna inom språkbehandling för dess sammanfattningar och svar. Resultatet är en applikation som når en nära mänsklig intuition för vissa domäner och frågor, som exempelvis Wikipedia- och nyhetsartiklar, samt viss vetensaplig text. Noterade undantag för tillämpningen härrör från ämnets komplexitet, grammatiska korrekthet för frågorna och dokumentets längd. Dessa är områden som kan förbättras ytterligare om den används i produktionen.
Usbeck, Ricardo. "Knowledge Extraction for Hybrid Question Answering." Doctoral thesis, Universitätsbibliothek Leipzig, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-225097.
Повний текст джерелаGlinos, Demetrios. "SYNTAX-BASED CONCEPT EXTRACTION FOR QUESTION ANSWERING." Doctoral diss., University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3565.
Повний текст джерелаPh.D.
School of Computer Science
Engineering and Computer Science
Computer Science
Mur, Jori. "Off-line answer extraction for question answering." [S.l. : [Groningen : s.n.] ; University Library Groningen] [Host], 2008. http://irs.ub.rug.nl/ppn/.
Повний текст джерелаKonstantinova, Natalia. "Knowledge acquisition from user reviews for interactive question answering." Thesis, University of Wolverhampton, 2013. http://hdl.handle.net/2436/297401.
Повний текст джерелаAlmansa, Luciana Farina. "Uma arquitetura de question-answering instanciada no domínio de doenças crônicas." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/95/95131/tde-10102016-121606/.
Повний текст джерелаThe medical record describes health conditions of patients helping experts to make decisions about the treatment. The biomedical scientific knowledge can improve the prevention and the treatment of diseases. However, the search for relevant knowledge may be a hard task because it is necessary time and the healthcare research is constantly updating. Many healthcare professionals have a stressful routine, because they work in different hospitals or medical offices, taking care many patients per day. The goal of this project is to design a Question Answering Framework to support faster and more precise searches for information in epigenetic, chronic disease and thyroid images. To develop the proposal, we are reusing two frameworks that have already developed: SisViDAS and FREDS. These two frameworks are being exploited to compose a document processing module. The other modules (question and answer processing) are being completely developed. The QASF was evaluated by a reference collection and performance measures. The results show 0.7 of precision and 0.3 of recall for two hundred articles retrieved. Considering that the questions inserted on the framework have an average of seventy terms, the QASF shows good results. This project intends to decrease search time once QA systems provide straight and precise answers in a process started by a user question in natural language
Usbeck, Ricardo [Verfasser], Klaus-Peter [Gutachter] Fähnrich, Philipp [Gutachter] Cimiano, Ngomo Axel-Cyrille [Akademischer Betreuer] Ngonga, and Klaus-Peter [Akademischer Betreuer] Fähnrich. "Knowledge Extraction for Hybrid Question Answering / Ricardo Usbeck ; Gutachter: Klaus-Peter Fähnrich, Philipp Cimiano ; Akademische Betreuer: Axel-Cyrille Ngonga Ngomo, Klaus-Peter Fähnrich." Leipzig : Universitätsbibliothek Leipzig, 2017. http://d-nb.info/1173734775/34.
Повний текст джерелаKrč, Martin. "Znalec encyklopedie." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2009. http://www.nusl.cz/ntk/nusl-236707.
Повний текст джерелаDeyab, Rodwan Bakkar. "Ontology-based information extraction from learning management systems." Master's thesis, Universidade de Évora, 2017. http://hdl.handle.net/10174/20996.
Повний текст джерелаBen, Abacha Asma. "Recherche de réponses précises à des questions médicales : le système de questions-réponses MEANS." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00735612.
Повний текст джерелаКниги з теми "Extractive Question-Answering"
Harabagiu, Sanda, and Dan Moldovan. Question Answering. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0031.
Повний текст джерелаPazienza, Maria Teresa. Information Extraction in the Web Era: Natural Language Communication for Knowledge Acquisition and Intelligent Information Agents. Springer London, Limited, 2006.
Знайти повний текст джерелаInformation Extraction in the Web Era: Natural Language Communication for Knowledge Acquisition and Intelligent Information Agents (Lecture Notes in Computer Science). Springer, 2003.
Знайти повний текст джерелаЧастини книг з теми "Extractive Question-Answering"
Jha, Raj, and V. Susheela Devi. "Extractive Question Answering Using Transformer-Based LM." In Communications in Computer and Information Science, 373–84. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1642-9_32.
Повний текст джерелаFerreira, Bruno Carlos Luís, Hugo Gonçalo Oliveira, Hugo Amaro, Ângela Laranjeiro, and Catarina Silva. "Evaluating the Extraction of Toxicological Properties with Extractive Question Answering." In Engineering Applications of Neural Networks, 599–606. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-34204-2_48.
Повний текст джерелаKabber, Anusha, V. M. Dhruthi, Raghav Pandit, and S. Natarajan. "Extractive Long-Form Question Answering for Annual Reports Using BERT." In Proceedings of Emerging Trends and Technologies on Intelligent Systems, 295–304. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4182-5_23.
Повний текст джерелаDu, Mingzhe, Mouad Hakam, See-Kiong Ng, and Stéphane Bressan. "Constituency-Informed and Constituency-Constrained Extractive Question Answering with Heterogeneous Graph Transformer." In Transactions on Large-Scale Data- and Knowledge-Centered Systems LIII, 90–106. Berlin, Heidelberg: Springer Berlin Heidelberg, 2023. http://dx.doi.org/10.1007/978-3-662-66863-4_4.
Повний текст джерелаSang, Erik Tjong Kim, Katja Hofmann, and Maarten de Rijke. "Extraction of Hypernymy Information from Text∗." In Interactive Multi-modal Question-Answering, 223–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17525-1_10.
Повний текст джерелаBouma, Gosse, Ismail Fahmi, and Jori Mur. "Relation Extraction for Open and Closed Domain Question Answering." In Interactive Multi-modal Question-Answering, 171–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17525-1_8.
Повний текст джерелаvan der Plas, Lonneke, Jörg Tiedemann, and Ismail Fahmi. "Automatic Extraction of Medical Term Variants from Multilingual Parallel Translations." In Interactive Multi-modal Question-Answering, 149–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17525-1_7.
Повний текст джерелаSrihari, Rohini K., Wei Li, and Xiaoge Li. "Question Answering Supported By Multiple Levels Of Information Extraction." In Advances in Open Domain Question Answering, 349–82. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-4746-6_11.
Повний текст джерелаLehmann, Jens, Tim Furche, Giovanni Grasso, Axel-Cyrille Ngonga Ngomo, Christian Schallhart, Andrew Sellers, Christina Unger, et al. "deqa: Deep Web Extraction for Question Answering." In The Semantic Web – ISWC 2012, 131–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35173-0_9.
Повний текст джерелаKontos, J., and I. Malagardi. "Question Answering and Information Extraction from Texts." In Advances in Intelligent Systems, 121–30. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4840-5_11.
Повний текст джерелаТези доповідей конференцій з теми "Extractive Question-Answering"
Wang, Luqi, Kaiwen Zheng, Liyin Qian, and Sheng Li. "A Survey of Extractive Question Answering." In 2022 International Conference on High Performance Big Data and Intelligent Systems (HDIS). IEEE, 2022. http://dx.doi.org/10.1109/hdis56859.2022.9991478.
Повний текст джерелаShymbayev, Magzhan, and Yermek Alimzhanov. "Extractive Question Answering for Kazakh Language." In 2023 IEEE International Conference on Smart Information Systems and Technologies (SIST). IEEE, 2023. http://dx.doi.org/10.1109/sist58284.2023.10223508.
Повний текст джерелаFajcik, Martin, Josef Jon, and Pavel Smrz. "Rethinking the Objectives of Extractive Question Answering." In Proceedings of the 3rd Workshop on Machine Reading for Question Answering. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.mrqa-1.2.
Повний текст джерелаArumae, Kristjan, and Fei Liu. "Guiding Extractive Summarization with Question-Answering Rewards." In Proceedings of the 2019 Conference of the North. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/n19-1264.
Повний текст джерелаLewis, Patrick, Barlas Oguz, Ruty Rinott, Sebastian Riedel, and Holger Schwenk. "MLQA: Evaluating Cross-lingual Extractive Question Answering." In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.acl-main.653.
Повний текст джерелаPrasad, Archiki, Trung Bui, Seunghyun Yoon, Hanieh Deilamsalehy, Franck Dernoncourt, and Mohit Bansal. "MeetingQA: Extractive Question-Answering on Meeting Transcripts." In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.acl-long.837.
Повний текст джерелаRakotoson, Loïc, Charles Letaillieur, Sylvain Massip, and Fréjus A. A. Laleye. "Extractive-Boolean Question Answering for Scientific Fact Checking." In ICMR '22: International Conference on Multimedia Retrieval. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3512732.3533580.
Повний текст джерелаVaranasi, Stalin, Saadullah Amin, and Guenter Neumann. "AutoEQA: Auto-Encoding Questions for Extractive Question Answering." In Findings of the Association for Computational Linguistics: EMNLP 2021. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.findings-emnlp.403.
Повний текст джерелаFrermann, Lea. "Extractive NarrativeQA with Heuristic Pre-Training." In Proceedings of the 2nd Workshop on Machine Reading for Question Answering. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-5823.
Повний текст джерелаDemner-Fushman, Dina, and Jimmy Lin. "Answer extraction, semantic clustering, and extractive summarization for clinical question answering." In the 21st International Conference. Morristown, NJ, USA: Association for Computational Linguistics, 2006. http://dx.doi.org/10.3115/1220175.1220281.
Повний текст джерелаЗвіти організацій з теми "Extractive Question-Answering"
Srihari, Rohini, and Wei Li. Information Extraction Supported Question Answering. Fort Belvoir, VA: Defense Technical Information Center, October 1999. http://dx.doi.org/10.21236/ada460042.
Повний текст джерела