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Barbara J. Grosz • Artificial Intelligence
(1982)
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DOI: https://doi.org/10.1016/0004-3702(82)90032-7
François Yvon • Lecture notes in computer science
(2023)
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Open Access
DOI: https://doi.org/10.1007/978-3-031-24349-3_6
Shazia A. Mitha, Jessica Schwartz, Mollie Hobensack, Kenrick Cato et al. • CIN Computers Informatics Nursing
(2022)
Natural language processing includes a variety of techniques that help to extract meaning from narrative data. In healthcare, medical natural language processing has been a growing field of study; however, little is known about its use in n...
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Open Access
DOI: https://doi.org/10.1097/cin.0000000000000967
PMC: 11499545
Diane J. Litman • Proceedings of the AAAI Conference on Artificial Intelligence
(2016)
Advances in natural language processing (NLP) and educational technology, as well as the availability of unprecedented amounts of educationally-relevant text and speech data, have led to an increasing interest in using NLP to address the ne...
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Open Access
DOI: https://doi.org/10.1609/aaai.v30i1.9879
Mallory Selfridge • Artificial Intelligence in Engineering
(1987)
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DOI: https://doi.org/10.1016/0954-1810(87)90076-8
V Geetha, C.K. Gomathy, Mr.D.Sri Datta Vallab Yaratha Yagn, Sai Praneesh • INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
(2023)
Natural Language Processing (NLP) is a rapidly evolving field in the intersection of computer science, artificial intelligence, and linguistics. This article provides an overview of NLP, tracing its historical development from early rule-ba...
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Open Access
DOI: https://doi.org/10.55041/ijsrem27094
Yijun Xiao, William Yang Wang • Proceedings of the AAAI Conference on Artificial Intelligence
(2019)
Reliable uncertainty quantification is a first step towards building explainable, transparent, and accountable artificial intelligent systems. Recent progress in Bayesian deep learning has made such quantification realizable. In this paper,...
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Open Access
DOI: https://doi.org/10.1609/aaai.v33i01.33017322
Renáta Németh, Júlia Koltai • Intersections
(2023)
Natural language processing (NLP) methods are designed to automatically process and analyze large amounts of textual data. The integration of this new-generation toolbox into sociology faces many challenges. NLP was institutionalized outsid...
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DOI: https://doi.org/10.17356/ieejsp.v9i1.871
Verónica Dahl • The Journal of Logic Programming
(1994)
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Open Access
DOI: https://doi.org/10.1016/0743-1066(94)90036-1
Stéphane M. Meystre, Peter John Haug • BMC Medical Informatics and Decision Making
(2005)
BACKGROUND: The medical problem list is an important part of the electronic medical record in development in our institution. To serve the functions it is designed for, the problem list has to be as accurate and timely as possible. However,...
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DOI: https://doi.org/10.1186/1472-6947-5-30
PMC: 1208893
Joydeep Bhattacharjee • Apress eBooks
(2019)
In the previous chapters, we took a look at different machine learning algorithms and then we worked on how to work with data for those algorithms. Those data sets were largely tabular, and the individual values were either numerical or cat...
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DOI: https://doi.org/10.1007/978-1-4842-5121-8_5
Ingrid Zukerman A, Diane J. Litman • User Modeling and User-Adapted Interaction
(2001)
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Open Access
DOI: https://doi.org/10.1023/a:1011174108613
Emily M. Bender, Batya Friedman • Transactions of the Association for Computational Linguistics
(2018)
In this paper, we propose data statements as a design solution and professional practice for natural language processing technologists, in both research and development. Through the adoption and widespread use of data statements, the field ...
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DOI: https://doi.org/10.1162/tacl_a_00041
Aleš Horák, Adam Rambousek • Routledge eBooks
(2017)
The chapter introduces links between lexicography and natural language processing in both directions. First, how the lexicographic work benefits from techniques of natural language processing such as word sense disambiguation, semantic simi...
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DOI: https://doi.org/10.4324/9781315104942-13
Xavier Vasques • Wiley eBooks
(2024)
This book chapter focuses on natural language processing (NLP) and covers various applications such as classifying messages as spam or ham, sentiment analysis, and the use of Bidirectional Encoder Representations from Transformers (BERT). T...
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DOI: https://doi.org/10.1002/9781394220649.ch4
Bonnie Lynn Nash-Webber, Roger C. Schank • Theoretical Issues In Natural Language Processing
(1975)
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Detmar Meurers • Cambridge University Press eBooks
(2015)
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DOI: https://doi.org/10.1017/cbo9781139649414.024
Yang Liu, Meng Zhang • Computational Linguistics
(2017)
Deep learning has attracted dramatic attention in recent years, both in academia and industry. The popular term deep learning generally refers to neural network methods. Indeed, many core ideas and methods were born years ago in the era of ...
OPENALEX
cc-by-nc-nd
DOI: https://doi.org/10.1162/coli_r_00312
Carly D. Robinson, Michael Yeomans, Justin Reich, Chris S. Hulleman et al. • International Conference on Learning Analytics and Knowledge (LAK)
(2016)
Student intention and motivation are among the strongest predictors of persistence and completion in Massive Open Online Courses (MOOCs), but these factors are typically measured through fixed-response items that constrain student expressio...
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DOI: https://doi.org/10.1145/2883851.2883932
Joseph P. Olive, Caitlin Christianson, John McCary • Springer eBooks
(2011)
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DOI: https://doi.org/10.1007/978-1-4419-7713-7