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Academic Articles & Research Papers
Showing 20 of 440 academic articles
Zhihui Song, Xin Zhou, Jinchen Xu, Xiaodong Ding et al. • Scientific Reports
(2024)
Abstract In recent years, deep learning has been widely used in vulnerability detection with remarkable results. These studies often apply natural language processing (NLP) technologies due to the natural similarity between code and languag...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-024-63021-y
Raviraju Balappa D, Gautam Kumar Rajput • Shodh Sari
(2025)
Matrices are foundational to artificial intelligence (AI), serving as critical tools for data representation, manipulation, and transformation across various applications. From machine learning algorithms to neural network architectures, ma...
DOAJ
Open Access (DOAJ)
DOI: https://doi.org/10.59231/SARI7840
Dylan Herman, Cody Googin, Xiaoyuan Liu, Alexey Galda et al. • RePEc: Research Papers in Economics
(2022)
Quantum computers are expected to surpass the computational capabilities of classical computers during this decade and have transformative impact on numerous industry sectors, particularly finance. In fact, finance is estimated to be the fi...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.2201.02773
Fabien Charmet, Harry Chandra Tanuwidjaja, Solayman Ayoubi, Pierre-François Gimenez et al. • Annals of Telecommunications
(2022)
Abstract With the extensive application of deep learning (DL) algorithms in recent years, e.g., for detecting Android malware or vulnerable source code, artificial intelligence (AI) and machine learning (ML) are increasingly becoming essent...
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DOI: https://doi.org/10.1007/s12243-022-00926-7
Peratham Wiriyathammabhum, Douglas A. Summers-Stay, Cornelia M. Fermuller, Yiannis Aloimonos • ACM Computing Surveys
(2016)
Integrating computer vision and natural language processing is a novel interdisciplinary field that has received a lot of attention recently. In this survey, we provide a comprehensive introduction of the integration of computer vision and ...
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DOI: https://doi.org/10.1145/3009906
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
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