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Showing 20 of 4,247 academic articles
Arjun Mohanakumar, Massimiliano Rinaldi, Jasmine Hadj Saadoun, Camilla Lazzi et al. • Applied Food Research
(2026)
Agri-food processing generates large volumes of by-products that remain insufficiently exploited despite their content of phenolic compounds, peptides, polysaccharides, carotenoids, dietary fibres and other functional constituents. These si...
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Open Access (DOAJ)
DOI: 10.1016/j.afres.2026.102511
Hang Li • National Science Review
(2017)
Deep learning refers to machine learning technologies for learning and utilizing ‘deep’ artificial neural networks, such as deep neural networks (DNN), convolutional neural networks (CNN) and recurrent neural networks (RNN). Recently, deep ...
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DOI: https://doi.org/10.1093/nsr/nwx110
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen et al. • arXiv (Cornell University)
(2011)
We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including: part-of-speech tagging, chunking, named entity recognition, and semantic role labeling. This...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1103.0398
Dirk Hovy, Shrimai Prabhumoye • Language and Linguistics Compass
(2021)
Recently, there has been an increased interest in demographically grounded bias in natural language processing (NLP) applications. Much of the recent work has focused on describing bias and providing an overview of bias in a larger context....
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DOI: https://doi.org/10.1111/lnc3.12432
PMC: 9285808
Quentin Lhoest, A. Villanova del Moral, Yacine Jernite, Abhishek Thakur et al. • Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP)
(2021)
Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, Abhishek Thakur, Patrick von Platen, Suraj Patil, Julien Chaumond, Mariama Drame, Julien Plu, Lewis Tunstall, Joe Davison, Mario Šaško, Gunjan Chhablani, Bhavitvya Malik, Simon Bra...
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DOI: https://doi.org/10.18653/v1/2021.emnlp-demo.21
Tristan Millington, Saturnino Luz • Frontiers in Computer Science
(2021)
In this paper we construct word co-occurrence networks from transcript data of controls and patients with potential Alzheimer’s disease using the ADReSS challenge dataset of spontaneous speech. We examine measures of the structure of these ...
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Open Access (DOAJ)
DOI: 10.3389/fcomp.2021.649508
Shahzeb Ansari, Haiping Du, Fazel Naghdy, Ayaz Ahmed Hoshu et al. • Safety
(2024)
Driver mental fatigue is considered a major factor affecting driver behavior that may result in fatal accidents. Several approaches are addressed in the literature to detect fatigue behavior in a timely manner through either physiological o...
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Open Access (DOAJ)
DOI: 10.3390/safety10010009
CHEN Ao, LI Chen, YAN Jiayun, PENG Liantie et al. • Kongzhi Yu Xinxi Jishu
(2024)
Standardization is one of the key steps to analyze locomotive overhaul data with a focus on reliability-centered maintenance (RCM). However, traditional manual methods encounter challenges such as small sample sizes, non-standardized data f...
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Open Access (DOAJ)
Ewoud Pons, Loes Braun, M. G. Myriam Hunink, Jan A. Kors • Radiology
(2016)
Radiological reporting has generated large quantities of digital content within the electronic health record, which is potentially a valuable source of information for improving clinical care and supporting research. Although radiology repo...
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DOI: https://doi.org/10.1148/radiol.16142770
Ronan Collobert, Jason Weston • International Conference on Machine Learning
(2008)
We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named entity tags, semantic roles, semantically similar words and the lik...
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DOI: https://doi.org/10.1145/1390156.1390177
Aravind K. Joshi • Science
(1991)
Natural language processing (NLP) is the study of mathematical and computational modeling of various aspects of language and the development of a wide range of systems. These include spoken language systems that integrate speech and natural...
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DOI: https://doi.org/10.1126/science.253.5025.1242
Kai Wang, Kunjian Wen, Yanping Chen, Yongbin Qin • Scientific Reports
(2025)
Abstract Mapping a sentence into a two-dimensional (2D) representation can flatten nested semantic structures and build multi-granular span dependencies in named entity recognition. Existing approaches to recognizing named entities often cl...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-87722-0
Saleh Rahimi, Faramarz Soheili • جامعه شناسی کاربردی
(2025)
IntroductionBibliometric analysis is widely acknowledged as a robust and systematic approach for examining extensive scholarly literature. It serves as a vital tool for mapping the landscape of contemporary research across various academic ...
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Open Access (DOAJ)
DOI: 10.22108/jas.2025.144379.2609
Aneeqa Ahmad, Musarrat Azher, Muhammad Asim Mahmood • NUML Journal of Critical Inquiry
(2025)
This study aims at investigating how humor is constructed in corporate memes through cognitive mechanisms and how corporate memes are used as a collective voice by Pakistani employees to express discontent with their work culture and organi...
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Open Access (DOAJ)
DOI: 10.52015/numljci.v23iII.296
Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, Thomas Wolf (2019)
The classic supervised machine learning paradigm is based on learning in isolation, a single predictive model for a task using a single dataset. This approach requires a large number of training examples and performs best for well-defined a...
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DOI: https://doi.org/10.18653/v1/n19-5004
Robert Dale, Hermann L. Moisl, HAROLD L. SOMERS • Computational Linguistics
(2001)
Symbolic approaches to natural language processing tokenisation and sentence segmentation lexical analysis parsing techniques semantic analysis discourse structure and intention recognition natural language generation intelligent writing as...
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Open Access
DOI: https://doi.org/10.1162/coli.2000.27.4.602
Wen-wai Yim, Meliha Yetişgen, William Proctor Harris, Sharon W. Kwan • JAMA Oncology
(2016)
IMPORTANCE: Natural language processing (NLP) has the potential to accelerate translation of cancer treatments from the laboratory to the clinic and will be a powerful tool in the era of personalized medicine. This technology can harvest im...
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DOI: https://doi.org/10.1001/jamaoncol.2016.0213
Andrea Galassi, Marco Lippi, Paolo Torroni • IEEE Transactions on Neural Networks and Learning Systems
(2020)
Attention is an increasingly popular mechanism used in a wide range of neural architectures. The mechanism itself has been realized in a variety of formats. However, because of the fast-paced advances in this domain, a systematic overview o...
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DOI: https://doi.org/10.1109/tnnls.2020.3019893
Gobinda G Chowdhury • Annual Review of Information Science and Technology
(2003)
Previous ARIST chapters (Haas, 1996;Warner, 1987) described a number of theoretical developments that have influenced research in NLP.The most recent theoretical developments can be grouped into four classes: (i) statistical and corpus-base...
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Open Access
DOI: https://doi.org/10.1002/aris.1440370103
Steven Bird, Ewan Klein, Edward Loper • CERN Document Server (European Organization for Nuclear Research)
(2009)
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'...
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