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Статті в журналах з теми "Events in natural language processing":
KARTTUNEN, LAURI, KIMMO KOSKENNIEMI, and GERTJAN VAN NOORD. "Finite state methods in natural language processing." Natural Language Engineering 9, no. 1 (March 2003): 1–3. http://dx.doi.org/10.1017/s1351324903003139.
Li, Yong, Xiaojun Yang, Min Zuo, Qingyu Jin, Haisheng Li, and Qian Cao. "Deep Structured Learning for Natural Language Processing." ACM Transactions on Asian and Low-Resource Language Information Processing 20, no. 3 (July 9, 2021): 1–14. http://dx.doi.org/10.1145/3433538.
Ozonoff, Al, Carly E. Milliren, Kerri Fournier, Jennifer Welcher, Assaf Landschaft, Mihail Samnaliev, Mehmet Saluvan, Mark Waltzman, and Amir A. Kimia. "Electronic surveillance of patient safety events using natural language processing." Health Informatics Journal 28, no. 4 (October 2022): 146045822211324. http://dx.doi.org/10.1177/14604582221132429.
Guda, Vanitha, and SureshKumar Sanampudi. "Event Time Relationship in Natural Language Text." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 7, no. 3 (September 25, 2019): 4. http://dx.doi.org/10.3991/ijes.v7i3.10985.
Balgi, Sanjana Madhav. "Fake News Detection using Natural Language Processing." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 4790–95. http://dx.doi.org/10.22214/ijraset.2022.45095.
Hkiri, Emna, Souheyl Mallat, and Mounir Zrigui. "Events Automatic Extraction from Arabic Texts." International Journal of Information Retrieval Research 6, no. 1 (January 2016): 36–51. http://dx.doi.org/10.4018/ijirr.2016010103.
Melton, Genevieve B., and George Hripcsak. "Automated Detection of Adverse Events Using Natural Language Processing of Discharge Summaries." Journal of the American Medical Informatics Association 12, no. 4 (July 2005): 448–57. http://dx.doi.org/10.1197/jamia.m1794.
YLI-JYRÄ, ANSSI, ANDRÁS KORNAI, and JACQUES SAKAROVITCH. "Finite-state methods and models in natural language processing." Natural Language Engineering 17, no. 2 (March 21, 2011): 141–44. http://dx.doi.org/10.1017/s1351324911000015.
Abbood, Auss, Alexander Ullrich, Rüdiger Busche, and Stéphane Ghozzi. "EventEpi—A natural language processing framework for event-based surveillance." PLOS Computational Biology 16, no. 11 (November 20, 2020): e1008277. http://dx.doi.org/10.1371/journal.pcbi.1008277.
Kosiv, Yurii A., and Vitaliy S. Yakovyna. "Three language political leaning text classification using natural language processing methods." Applied Aspects of Information Technology 5, no. 4 (December 28, 2022): 359–70. http://dx.doi.org/10.15276/aait.05.2022.24.
Дисертації з теми "Events in natural language processing":
Patil, Supritha Basavaraj. "Analysis of Moving Events Using Tweets." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/90884.
Master of Science
News now travels faster on social media than through news channels. Information from social media can help retrieve minute details that might not be emphasized in news. People tend to describe their actions or sentiments in tweets. I aim at studying if such collections of tweets are dependable sources for identifying paths of moving events. In events like hurricanes, using Twitter can help in analyzing people’s reaction to such moving events. These may include actions such as dislocation or emotions during different phases of the event. The results obtained in the experiments concur with the actual path of the events with respect to the regions affected and time. The frequency of tweets increases during event peaks. The number of locations affected that are identified are significantly more than in news wires.
Huang, Yin Jou. "Event Centric Approaches in Natural Language Processing." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/265210.
Nothman, Joel. "Grounding event references in news." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/10609.
Lindén, Johannes. "Huvudtitel: Understand and Utilise Unformatted Text Documents by Natural Language Processing algorithms." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-31043.
Sanagavarapu, Krishna Chaitanya. "Determining Whether and When People Participate in the Events They Tweet About." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984235/.
Sakaguchi, Tomohiro. "Anchoring Events to the Time Axis toward Storyline Construction." Kyoto University, 2019. http://hdl.handle.net/2433/242437.
Kyoto University (京都大学)
0048
新制・課程博士
博士(情報学)
甲第21912号
情博第695号
新制||情||119(附属図書館)
京都大学大学院情報学研究科知能情報学専攻
(主査)教授 黒橋 禎夫, 教授 西田 豊明, 教授 楠見 孝
学位規則第4条第1項該当
Baier, Thomas, Ciccio Claudio Di, Jan Mendling, and Mathias Weske. "Matching events and activities by integrating behavioral aspects and label analysis." Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/s10270-017-0603-z.
Mills, Michael Thomas. "Natural Language Document and Event Association Using Stochastic Petri Net Modeling." Wright State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=wright1369408524.
Mehta, Sneha. "Towards Explainable Event Detection and Extraction." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/104359.
Doctor of Philosophy
Event extraction is the task of extracting events of societal importance from natural language texts. The task has a wide range of applications from search, retrieval, question answering to forecasting population level events like civil unrest, disease occurrences with reasonable accuracy. Before events can be extracted it is imperative to identify the documents that are likely to contain the events of interest and extract the sentences that mention those events. This is termed as event detection. Current approaches for event detection are suboptimal. They assume that events are neatly partitioned into sentences and obtain document level event probabilities directly from predicted sentence level probabilities. In this dissertation, under the same assumption by leveraging representation learning we mitigate some of the shortcomings of the previous event detection methods. Current approaches to event extraction are only limited to restricted domains and require finegrained labeled corpora for their training. One way to extend event extraction to new domains in by enabling zero-shot extraction. Machine reading comprehension(MRC) based approach provides a promising way forward for zero-shot extraction. However, this approach suffers from the long-range dependency problem and faces difficulty in handling syntactically complex sentences with multiple clauses. To mitigate this problem we propose a syntactic sentence simplification algorithm that is guided by the MRC system to improves its performance.
Veladas, Rute Gomes. "Classificação automática de eventos na linha de saúde SNS24." Master's thesis, Universidade de Évora, 2021. http://hdl.handle.net/10174/29055.
Книги з теми "Events in natural language processing":
Frank, Schilder, Katz Graham, and Pustejovsky J, eds. Annotating, extracting and reasoning about time and events: International seminar, Dagstuhl Castle, Germany, April 10-15, 2005 : revised papers. Berlin: Springer, 2007.
Peterson, Philip L. Fact proposition event. Dordrecht: Kluwer Academic Publishers, 1997.
1961-, Allan James, ed. Topic detection and tracking: Event-based information organization. Boston: Kluwer Academic Publishers, 2002.
Filgueiras, M., L. Damas, N. Moreira, and A. P. Tomás, eds. Natural Language Processing. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/3-540-53678-7.
Noble, H. M. Natural language processing. Oxford, OX: Blackwell Scientific Publications, 1988.
Allan, James. Topic Detection and Tracking: Event-based Information Organization. Boston, MA: Springer US, 2002.
Kulkarni, Akshay, and Adarsha Shivananda. Natural Language Processing Recipes. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-7351-7.
Kulkarni, Akshay, Adarsha Shivananda, and Anoosh Kulkarni. Natural Language Processing Projects. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-7386-9.
Søgaard, Anders. Explainable Natural Language Processing. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-031-02180-0.
Tapsai, Chalermpol, Herwig Unger, and Phayung Meesad. Thai Natural Language Processing. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-56235-9.
Частини книг з теми "Events in natural language processing":
Jean-Louis, Ludovic, Romaric Besançon, and Olivier Ferret. "Using Temporal Cues for Segmenting Texts into Events." In Advances in Natural Language Processing, 150–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14770-8_18.
Vanetik, Natalia, Marina Litvak, and Efi Levi. "Real-World Events Discovering with TWIST." In Natural Language Processing for Electronic Design Automation, 71–107. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52273-5_4.
Ma, Xiao, Elnaz Davoodi, Leila Kosseim, and Nicandro Scarabeo. "Semantic Mapping of Security Events to Known Attack Patterns." In Natural Language Processing and Information Systems, 91–98. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91947-8_10.
Hürriyetoǧlu, Ali, Nelleke Oostdijk, Mustafa Erkan Başar, and Antal van den Bosch. "Supporting Experts to Handle Tweet Collections About Significant Events." In Natural Language Processing and Information Systems, 138–41. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59569-6_14.
Hürriyetoǧlu, Ali, Nelleke Oostdijk, and Antal van den Bosch. "Estimating Time to Event of Future Events Based on Linguistic Cues on Twitter." In Intelligent Natural Language Processing: Trends and Applications, 67–97. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67056-0_5.
Barik, Biswanath, Erwin Marsi, and Pinar Öztürk. "Extracting Causal Relations Among Complex Events in Natural Science Literature." In Natural Language Processing and Information Systems, 131–37. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59569-6_13.
Filatova, Elena, and Vasileios Hatzivassiloglou. "Marking atomic events in sets of related texts." In Recent Advances in Natural Language Processing III, 247. Amsterdam: John Benjamins Publishing Company, 2004. http://dx.doi.org/10.1075/cilt.260.27fil.
Tsolmon, Bayar, A.-Rong Kwon, and Kyung-Soon Lee. "Extracting Social Events Based on Timeline and Sentiment Analysis in Twitter Corpus." In Natural Language Processing and Information Systems, 265–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31178-9_32.
Arnulphy, Béatrice, Vincent Claveau, Xavier Tannier, and Anne Vilnat. "Supervised Machine Learning Techniques to Detect TimeML Events in French and English." In Natural Language Processing and Information Systems, 19–32. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19581-0_2.
Loukachevitch, Natalia, and Boris Dobrov. "RuThes Thesaurus for Natural Language Processing." In The Palgrave Handbook of Digital Russia Studies, 319–34. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42855-6_18.
Тези доповідей конференцій з теми "Events in natural language processing":
Chen, Muhao, Hongming Zhang, Qiang Ning, Manling Li, Heng Ji, Kathleen McKeown, and Dan Roth. "Event-Centric Natural Language Processing." In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Tutorial Abstracts. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.acl-tutorials.2.
Velichkov, Boris, Ivan Koychev, and Svetla Boytcheva. "Deep Learning Contextual Models for Prediction of Sport Events Outcome from Sportsmen Interviews." In Recent Advances in Natural Language Processing. Incoma Ltd., Shoumen, Bulgaria, 2019. http://dx.doi.org/10.26615/978-954-452-056-4_142.
"Computing Implicit Entities and Events with Getaruns." In International Workshop on Natural Language Processing and Cognitive Science. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0002171600230035.
Zhang, Zheng, Tianjun Hou, Josselin Kherroubi, and Daria Khvostichenko. "Event Detection in Drilling Remarks Using Natural Language Processing." In IADC/SPE International Drilling Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/208779-ms.
Loukachevitch, Natalia, Ekaterina Artemova, Tatiana Batura, Pavel Braslavski, Ilia Denisov, Vladimir Ivanov, Suresh Manandhar, Alexander Pugachev, and Elena Tutubalina. "NEREL: A Russian Dataset with Nested Named Entities, Relations and Events." In International Conference Recent Advances in Natural Language Processing. INCOMA Ltd. Shoumen, BULGARIA, 2021. http://dx.doi.org/10.26615/978-954-452-072-4_100.
Choubey, Prafulla Kumar, and Ruihong Huang. "Event Coreference Resolution by Iteratively Unfolding Inter-dependencies among Events." In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/d17-1226.
Hu, Hangping, Zhen Zhang, Weijian Qin, Yuan Wang, and Xiaojian Li. "A Survey of Cloud Service Events and Their Connections." In 8th International Conference on Natural Language Processing (NATP 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120108.
Xie, Xi Hai, and Le Chen. "Analysis of Sentiment Tendency Based on Major Public Health Events." In 2022 4th International Conference on Natural Language Processing (ICNLP). IEEE, 2022. http://dx.doi.org/10.1109/icnlp55136.2022.00093.
Yang, Erhong, Qingqing Zeng, and Danqing Zhu. "Analysis about event annotation and information structure in sudden events discourse." In 2009 International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE). IEEE, 2009. http://dx.doi.org/10.1109/nlpke.2009.5313778.
Chaney, Allison, Hanna Wallach, Matthew Connelly, and David Blei. "Detecting and Characterizing Events." In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2016. http://dx.doi.org/10.18653/v1/d16-1122.
Звіти організацій з теми "Events in natural language processing":
DANIELSON, THOMAS. NATURAL LANGUAGE PROCESSING FOR TEXT- BASED EVENT EXTRACTION: IDENTIFYING EVENTS OF INTEREST RELATED TO WORLDWIDE STATE-SPONSORED CIVIL NUCLEAR POWER. Office of Scientific and Technical Information (OSTI), March 2023. http://dx.doi.org/10.2172/1962589.
Steedman, Mark. Natural Language Processing. Fort Belvoir, VA: Defense Technical Information Center, June 1994. http://dx.doi.org/10.21236/ada290396.
Leavy, Michelle B., Danielle Cooke, Sarah Hajjar, Erik Bikelman, Bailey Egan, Diana Clarke, Debbie Gibson, Barbara Casanova, and Richard Gliklich. Outcome Measure Harmonization and Data Infrastructure for Patient-Centered Outcomes Research in Depression: Report on Registry Configuration. Agency for Healthcare Research and Quality (AHRQ), November 2020. http://dx.doi.org/10.23970/ahrqepcregistryoutcome.
Tratz, Stephen C. Arabic Natural Language Processing System Code Library. Fort Belvoir, VA: Defense Technical Information Center, June 2014. http://dx.doi.org/10.21236/ada603814.
Wilks, Yorick, Michael Coombs, Roger T. Hartley, and Dihong Qiu. Active Knowledge Structures for Natural Language Processing. Fort Belvoir, VA: Defense Technical Information Center, January 1991. http://dx.doi.org/10.21236/ada245893.
Firpo, M. Natural Language Processing as a Discipline at LLNL. Office of Scientific and Technical Information (OSTI), February 2005. http://dx.doi.org/10.2172/15015192.
Anderson, Thomas. State of the Art of Natural Language Processing. Fort Belvoir, VA: Defense Technical Information Center, November 1987. http://dx.doi.org/10.21236/ada188112.
Hobbs, Jerry R., Douglas E. Appelt, John Bear, Mabry Tyson, and David Magerman. Robust Processing of Real-World Natural-Language Texts. Fort Belvoir, VA: Defense Technical Information Center, January 1991. http://dx.doi.org/10.21236/ada258837.
Neal, Jeannette G., Elissa L. Feit, Douglas J. Funke, and Christine A. Montgomery. An Evaluation Methodology for Natural Language Processing Systems. Fort Belvoir, VA: Defense Technical Information Center, December 1992. http://dx.doi.org/10.21236/ada263301.
Lehnert, Wendy G. Using Case-Based Reasoning in Natural Language Processing. Fort Belvoir, VA: Defense Technical Information Center, June 1993. http://dx.doi.org/10.21236/ada273538.