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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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Georgiana Țucudean, Marian Bucos, Bogdan Drăgulescu, Cătălin Daniel Căleanu • PeerJ Computer Science
(2024)
Natural language processing (NLP) tasks can be addressed with several deep learning architectures, and many different approaches have proven to be efficient. This study aims to briefly summarize the use cases for NLP tasks along with the ma...
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cc-by
DOI: https://doi.org/10.7717/peerj-cs.2222
PMC: 11322986
Jantima Polpinij, Manasawee Kaenampornpan, Christopher S. G. Khoo, Wei-Ning Cheng et al. • Mathematics
(2026)
Extracting and organizing knowledge from the agricultural crop disease research literature are challenging tasks because of the heterogeneous terminologies, complicated symptom descriptions, and unstructured nature of scientific documents. ...
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Open Access (DOAJ)
DOI: 10.3390/math14020299
Imran Mirza, Akbar Anbar Jafari, Cagri Ozcinar, Gholamreza Anbarjafari • Information
(2025)
Large language models (LLMs) have revolutionized natural language processing across diverse domains, yet they also raise critical fairness and ethical concerns, particularly regarding gender bias. In this study, we conduct a systematic, mat...
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Open Access (DOAJ)
DOI: 10.3390/info16050358
Cyrille YetuYetu Kesiku, Andrea Chaves-Villota, Begonya Garcia-Zapirain • Information
(2022)
The classification of biomedical literature is engaged in a number of critical issues that physicians are expected to answer. In many cases, these issues are extremely difficult. This can be conducted for jobs such as diagnosis and treatmen...
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Open Access (DOAJ)
DOI: 10.3390/info13100499
Adwait Ratnaparkhi • Scholarly Commons (University of Pennsylvania)
(1997)
Many problems in natural language processing can be viewed as linguistic classification problems, in which linguistic contexts are used to predict linguistic classes. Maximum entropy models offer a clean way to combine diverse pieces of con...
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Open Access
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
Peter E. Jackson, Isabelle Moulinier • Natural language processing
(2002)
Technology practitioners in the Internet space are constantly faced with difficult decision-making as to what research has been done and what the best practices are. This lucid text covers the emerging technologies of document retrieval, in...
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DOI: https://doi.org/10.1075/nlp.5(1st)
Chenglong Dao, Jun Qi • Buildings
(2024)
Urban blue–green spaces (UBGSs) are a significant avenue for addressing the worldwide mental health crisis. To effectively optimise landscape design and management for the promotion of health benefits from UBGS, it is crucial to objectively...
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Open Access (DOAJ)
DOI: 10.3390/buildings14051426
Yu Zhang, Lin Zhao, Shiyuan Hu • Scientific Reports
(2025)
Abstract Scientific assessment of cultural ecosystem services (CESs) levels in urban parks and refined analysis of their spatial equity are essential for residents’ social well-being. However, traditional assessment methods often fail to ca...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-18288-0
Cristian Cosentino, Simone Gatto, Pietro Liò, Fabrizio Marozzo • Future Internet
(2026)
Machine Learning (ML) models trained on large-scale datasets learn useful predictive patterns, but they may also memorize undesired information, leading to risks such as information leakage, bias, copyright violations, and privacy attacks. ...
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Open Access (DOAJ)
DOI: 10.3390/fi18030174
Rishi V. Parikh, Alan S. Go, Ankeet S. Bhatt, Thida C. Tan et al. • Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
(2023)
Background There is a need to develop electronic health record–based predictive models for worsening heart failure (WHF) events across clinical settings and across the spectrum of left ventricular ejection fraction (LVEF). Methods and Resul...
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Open Access (DOAJ)
DOI: 10.1161/JAHA.122.029736
Elsa Olivetti, Jacqueline M. Cole, Edward Kim, Olga Kononova et al. • Applied Physics Reviews
(2020)
Given the emergence of data science and machine learning throughout all aspects of society, but particularly in the scientific domain, there is increased importance placed on obtaining data. Data in materials science are particularly hetero...
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other-oa
DOI: https://doi.org/10.1063/5.0021106
Saima aslam • بازیافت
(2023)
Eco-criticism is relatively considered a new term in Urdu literature although a brief review of Urdu literature particularly poetry indicates that environmental problems have always been critically observed by the literary minds. Eco...
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Open Access (DOAJ)
DOI: 10.57156/bazyaft4216017
Yue Zhao • Discover Artificial Intelligence
(2026)
Abstract The growing variety of student profiles in higher education has made it more important than ever to have smart systems that can change learning experiences on the job. Current recommendation algorithms fail to capture the complex r...
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Open Access (DOAJ)
DOI: 10.1007/s44163-026-01500-z
Ralph Weischedel, J Carbonell, Barbara J. Grosz, W. Lehnert et al. • Annual Review of Computer Science
(1990)
From the Publisher:
These ten contributions describe the major technical ideas underlying many of the significant advances in natural language processing over the last decade, focusing in particular on the challenges in areas such as knowl...
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DOI: https://doi.org/10.1146/annurev.cs.04.060190.002251
Michał Wawer, Jarosław A. Chudziak, Ewa Niewiadomska-Szynkiewicz • Applied Sciences
(2024)
Traditional technical analysis methods face limitations in accurately predicting trends in today’s complex financial markets. Meanwhile, existing AI-driven approaches, while powerful in processing large datasets, often lack interpretability...
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Open Access (DOAJ)
DOI: 10.3390/app142411897
Drisceince MUTINDU CLAUDE, Raoul KIENGE-KIENGE INTUDI & Joël NZAMPUNGU IMBOLE • Ziglôbitha
(2026)
Résumé : Cette étude analyse la transformation de l’Inspection Générale des Finances (IGF) de la RDC à travers les réformes de 2020-2023 et l’annonce de son plan stratégique 2025-2027 articulant contrôle systémique et digitalisation. A part...
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Open Access (DOAJ)
DOI: 10.60632/ziglobitha.n018.23.vol.3.2026
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