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Showing 20 of 4,247 academic articles
Saqib Saeed, Salha A. Altamimi, Norah A. Alkayyal, Ebtisam Alshehri et al. • Sensors
(2023)
This systematic literature review explores the digital transformation (DT) and cybersecurity implications for achieving business resilience. DT involves transitioning organizational processes to IT solutions, which can result in significant...
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DOI: https://doi.org/10.3390/s23156666
PMC: 10422504
Abdalmuttaleb M. A. Musleh Al-Sartawi • International Journal of Critical Infrastructures
(2020)
Security breaches are very costly in the USA, followed very closely by the Middle East. Shareholders and investors demand that their firms mitigate all kinds of risks, and it is the responsibility of the BOD to gain and maintain their confi...
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DOI: https://doi.org/10.1504/ijcis.2020.10029173
Rafael A. Calvo, David Milne, M. Sazzad Hussain, Helen M Christensen • Natural Language Engineering
(2017)
Abstract Natural language processing (NLP) techniques can be used to make inferences about peoples’ mental states from what they write on Facebook, Twitter and other social media. These inferences can then be used to create online pathways ...
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DOI: https://doi.org/10.1017/s1351324916000383
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
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
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
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
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 ...
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DOI: https://doi.org/10.1162/coli_r_00312
Jonah A. Berger, Grant M. Packard • American Psychologist
(2021)
Language can provide important insights into people, and culture more generally. Further, the digitization of information has made more and more textual data available. But by itself, all that data are just that: data. Realizing its potenti...
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Open Access
DOI: https://doi.org/10.1037/amp0000882
John P Pestian, Henry A. Nasrallah, Paweł Matykiewicz, Aurora J. Bennett et al. • Biomedical Informatics Insights
(2010)
Suicide is the second leading cause of death among 25-34 year olds and the third leading cause of death among 15-25 year olds in the United States. In the Emergency Department, where suicidal patients often present, estimating the risk of r...
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DOI: https://doi.org/10.4137/bii.s4706
PMC: 3107011
Zhiyuan Liu, Yankai Lin, Maosong Sun • Springer eBooks
(2020)
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for NLP. It also benefit related domains such as machine learning, social network analysis, semantic Web, infor...
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DOI: https://doi.org/10.1007/978-981-15-5573-2
Vivi Năstase, Rada F. Mihalcea, Dragomir Radev • Natural Language Engineering
(2015)
Abstract Graphs are a powerful representation formalism that can be applied to a variety of aspects related to language processing. We provide an overview of how Natural Language Processing problems have been projected into the graph framew...
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Open Access
DOI: https://doi.org/10.1017/s1351324915000340
Arvind Chandrasekaran • International Journal on Cybernetics & Informatics
(2023)
Hints of the outbreak are detected through the modified circumstances favoring the outbreaks, like the warm weather contributing to epidermal outbreaks or the loss of sanitation leading to cholera outbreaks typically relying on the routine ...
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Open Access
DOI: https://doi.org/10.5121/ijci.2023.120205
(2008)
Welcome to the 2008 Conference on Empirical Methods in Natural Language Processing! The conference is organized under the auspices of SIGDAT, the ACL Special Interest Group for linguistic data and corpus-based approaches to natural language...
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DOI: https://doi.org/10.3115/1613715
Mitchell P. Marcus • Proceedings of the National Academy of Sciences
(1995)
The field of natural language processing (NLP) has seen a dramatic shift in both research direction and methodology in the past several years. In the past, most work in computational linguistics tended to focus on purely symbolic methods. R...
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Open Access
DOI: https://doi.org/10.1073/pnas.92.22.10052
PMC: 40734
Fredrik Olsson • KTH Publication Database DiVA (KTH Royal Institute of Technology)
(2009)
Active learning is a supervised machine learning technique in which the learner is in control of the data used for learning. That control is utilized by the learner to ask an oracle, typically a human with extensive knowledge of the domain ...
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