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Academic Articles & Research Papers
Showing 20 of 621 academic articles
Luciano Ignaczak, Guilherme Goldschmidt, Cristiano André da Costa, Rodrigo da Rosa Righi • ACM Computing Surveys
(2021)
The growth of data volume has changed cybersecurity activities, demanding a higher level of automation. In this new cybersecurity landscape, text mining emerged as an alternative to improve the efficiency of the activities involving unstruc...
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DOI: https://doi.org/10.1145/3462477
Fábio Eid Morooka, Adalberto Manoel Junior, Tiago F. A. C. Sigahi, Jefferson de Souza Pinto et al. • Machine Learning and Knowledge Extraction
(2023)
Applications of deep learning (DL) in autonomous vehicle (AV) projects have gained increasing interest from both researchers and companies. This has caused a rapid expansion of scientific production on DL-AV in recent years, encouraging res...
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Open Access (DOAJ)
DOI: 10.3390/make5030041
Olusola Bamisile, Dongsheng Cai, Humphrey Adun, Chukwuebuka Ejiyi et al. • Energy Reports
(2023)
The need to reduce global carbon emissions has led to a significant increase in clean energy globally. While renewable energy penetration into energy grids and power systems is increasing in many countries, the intermittency and stochastic ...
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Open Access (DOAJ)
DOI: 10.1016/j.egyr.2023.05.229
Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi et al. • Communications Materials
(2022)
Machine learning plays an increasingly important role in many areas of chemistry and materials science, being used to predict materials properties, accelerate simulations, design new structures, and predict synthesis routes of new materials...
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DOI: https://doi.org/10.1038/s43246-022-00315-6
PMC: 9702700
Valery Dmitrievich Solovyev, Marina Ivanovna Solnyshkina, Danielle S. McNamara • Russian Journal of Linguistics
(2022)
The dramatic expansion of modern linguistic research and enhanced accuracy of linguistic analysis have become a reality due to the ability of artificial neural networks not only to learn and adapt, but also carry out automate linguistic ana...
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Open Access (DOAJ)
DOI: 10.22363/2687-0088-31326
Kai-Wei Chang, Vinod M. Prabhakaran, Vicente Ordóñez • Conference on Empirical Methods in Natural Language Processing (EMNLP)
(2019)
Recent advances in data-driven machine learning techniques (e.g., deep neural networks) have revolutionized many natural language processing applications. These approaches automatically learn how to make decisions based on the statistics an...
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Jianye Xie, Yulan Zhang, Huaizhen Kou, Xiaoran Zhao et al. • Tsinghua Science and Technology
(2025)
Event extraction is an important part of natural language information extraction, and it’s widely employed in other natural language processing tasks including question answering and machine reading comprehension. However, there is a lack o...
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Open Access (DOAJ)
DOI: 10.26599/TST.2023.9010139
Zhewei Zhang, Huzi Cheng, Tianming Yang • PLoS Computational Biology
(2020)
The brain makes flexible and adaptive responses in a complicated and ever-changing environment for an organism's survival. To achieve this, the brain needs to understand the contingencies between its sensory inputs, actions, and rewards. Th...
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Open Access (DOAJ)
DOI: 10.1371/journal.pcbi.1008342
Jonas Rieger, Kostiantyn Yanchenko, Mattes Ruckdeschel, Gerret von Nordheim et al. • Studies in Communication, Media
(2024)
Pre-trained language models (PLM) based on transformer neural networks developed in the field of natural language processing (NLP) offer great opportunities to improve automatic content analysis in communication science, especially for the ...
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Open Access (DOAJ)
DOI: 10.5771/2192-4007-2024-1-72
Arezo Shakeri, Mina Farmanbar • Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring
(2025)
Abstract INTRODUCTION Alzheimer's disease (AD) prevalence is increasing, with no current cure. Natural language processing (NLP) offers the potential for non‐invasive diagnostics, social burden assessment, and research advancements in AD. M...
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Open Access (DOAJ)
DOI: 10.1002/dad2.70082
Albert Ntumba Nkongolo, Yae Olatoundji Gaba, Kafunda Katalay Pierre, Esther Matendo Mabela et al. • Journal of Innovation Information Technology and Application
(2025)
This study explores the application of natural language processing (NLP) techniques in financial time series forecasting, specifically in predicting stock prices. Historical stock price data and textual data from financial news articles and...
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Open Access (DOAJ)
DOI: 10.35970/jinita.v7i1.2290
Shima Javanmardi, Ali Mohammad Latif, Mohammad Taghi Sadeghi, Mehrdad Jahanbanifard et al. • Sensors
(2022)
In image captioning models, the main challenge in describing an image is identifying all the objects by precisely considering the relationships between the objects and producing various captions. Over the past few years, many methods have b...
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Open Access (DOAJ)
DOI: 10.3390/s22218376
Simov Kiril, Osenova Petya • Cybernetics and Information Technologies
(2018)
With the availability of large language data online, cross-linked lexical resources (such as BabelNet, Predicate Matrix and UBY) and semantically annotated corpora (SemCor, OntoNotes, etc.), more and more applications in Natural Language Pr...
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Open Access (DOAJ)
DOI: 10.2478/cait-2018-0008
Wenpeng Yin, Katharina Kann, Mo Yu, Hinrich Schütze • arXiv (Cornell University)
(2017)
Deep neural networks (DNN) have revolutionized the field of natural language processing (NLP). Convolutional neural network (CNN) and recurrent neural network (RNN), the two main types of DNN architectures, are widely explored to handle var...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1702.01923
Wei Emma Zhang, Quan Z. Sheng, Ahoud Alhazmi, Chenliang Li • ACM Transactions on Intelligent Systems and Technology
(2020)
With the development of high computational devices, deep neural networks (DNNs), in recent years, have gained significant popularity in many Artificial Intelligence (AI) applications. However, previous efforts have shown that DNNs are vulne...
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Open Access
DOI: https://doi.org/10.1145/3374217
Yue Zhang, Zhiyang Teng • Cambridge University Press eBooks
(2020)
With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are sy...
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DOI: https://doi.org/10.1017/9781108332873
Wazir Ali, Jay Kumar, Zenglin Xu, Rajesh Kumar et al. • Applied Sciences
(2021)
Named entity recognition (NER) is a fundamental task in many natural language processing (NLP) applications, such as text summarization and semantic information retrieval. Recently, deep neural networks (NNs) with the attention mechanism yi...
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Open Access (DOAJ)
DOI: 10.3390/app11199038
Mariya Toneva, Leila Wehbe • arXiv (Cornell University)
(2019)
Neural networks models for NLP are typically implemented without the explicit encoding of language rules and yet they are able to break one performance record after another. This has generated a lot of research interest in interpreting the ...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1905.11833
Jiang Du, Qiang Wei, Yisen Wang, Xingyu Bai • Entropy
(2025)
Recent advances in graph neural networks have transformed structural pattern learning in domains ranging from social network analysis to biomolecular modeling. Nevertheless, practical deployments in mission-critical scenarios such as binary...
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Open Access (DOAJ)
DOI: 10.3390/e27040392
Muhammad Shoaib Farooq, Syed Muhammad Asadullah Gilani, Muhammad Faraz Manzoor, Momina Shaheen • Information
(2025)
Fake news is false or misleading information that looks like real news and spreads through traditional and social media. It has a big impact on our social lives, especially in politics. In Pakistan, where Urdu is the main language, finding ...
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Open Access (DOAJ)
DOI: 10.3390/info16070595