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TransKGQA: Enhanced Knowledge Graph Question Answering With Sentence Transformers

You Li Chong, Chin Poo Lee, Shahrin Zen Muhd-Yassin, Kian Ming Lim et al. • IEEE Access (2024)

Knowledge Graph Question Answering (KGQA) plays a crucial role in extracting valuable insights from interconnected information. Existing methods, while commendable, face challenges such as contextual ambiguity and limited adaptability to di...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3405583

Computational linguistics and discourse complexology: Paradigms and research methods

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...

DOAJ Open Access (DOAJ) DOI: 10.22363/2687-0088-31326

Classifying Characteristics of Opioid Use Disorder From Hospital Discharge Summaries Using Natural Language Processing

Melissa N. Poulsen, Philip J. Freda, Vanessa Troiani, Anahita Davoudi et al. • Frontiers in Public Health (2022)

BackgroundOpioid use disorder (OUD) is underdiagnosed in health system settings, limiting research on OUD using electronic health records (EHRs). Medical encounter notes can enrich structured EHR data with documented signs and symptoms of O...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpubh.2022.850619

Language in Education Policy Debates in Africa Today

Prosperous Nankindu, Henry Hollan Ssembatya • Journal of Linguistics, Literary and Communication Studies (2026)

Through critical research methods using document analysis, this study investigated the current Language in Education Policy (LiEP) debates in Africa. There are many such debates going on across the continent, but the literature available is...

DOAJ Open Access (DOAJ) DOI: 10.58721/jllcs.v5i1.1592

Bias and Fairness in Natural Language Processing

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...

OPENALEX

Natural language processing with transformers: a review

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...

OPENALEX cc-by DOI: https://doi.org/10.7717/peerj-cs.2222 PMC: 11322986

Natural Language Processing and Semantical Representation of Medical Texts

Robert H Baud, A M Rassinoux, Jean Raoul Scherrer • Methods of Information in Medicine (1992)

For medical records, the challenge for the present decade is Natural Language Processing (NLP) of texts, and the construction of an adequate Knowledge Representation. This article describes the components of an NLP system, which is currentl...

OPENALEX DOI: https://doi.org/10.1055/s-0038-1634865

A bibliometric analysis of natural language processing in medical research

Xieling Chen, Haoran Xie, Fu Lee Wang, Ziqing Liu et al. • BMC Medical Informatics and Decision Making (2018)

BACKGROUND: Natural language processing (NLP) has become an increasingly significant role in advancing medicine. Rich research achievements of NLP methods and applications for medical information processing are available. It is of great sig...

OPENALEX cc-by DOI: https://doi.org/10.1186/s12911-018-0594-x PMC: 5872501

Enhancing sentiment classification on small datasets through data augmentation and transfer learning

Mahmoud S. Mayaleh, Samer A. Mayaleh • Discover Artificial Intelligence (2026)

Abstract Small-scale sentiment classification often suffers from data scarcity, which limits the generalization ability of the models. This study evaluates and compares the effectiveness of three data augmentation strategies: Easy Data Augm...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-025-00813-9

A Multi-Stage NLP Framework for Knowledge Discovery from Crop Disease Research Literature

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. ...

DOAJ Open Access (DOAJ) DOI: 10.3390/math14020299

D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction

Yuan Huang, Zhixing Li, Wei Deng, Guoyin Wang et al. • CAAI Transactions on Intelligence Technology (2021)

Abstract Relation extraction between entity pairs is an increasingly critical area in natural language processing. Recently, the pre‐trained bidirectional encoder representation from transformer (BERT) performs excellently on the text class...

DOAJ Open Access (DOAJ) DOI: 10.1049/cit2.12033

Natural Language Processing Techniques for Text Classification of Biomedical Documents: A Systematic Review

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...

DOAJ Open Access (DOAJ) DOI: 10.3390/info13100499

Unlocking Clinical Data from Narrative Reports: A Study of Natural Language Processing

George M. Hripcsak, Carol Friedman, Philip O. Alderson, William DuMouchel et al. • Annals of Internal Medicine (1995)

OBJECTIVE: To evaluate the automated detection of clinical conditions described in narrative reports. DESIGN: Automated methods and human experts detected the presence or absence of six clinical conditions in 200 admission chest radiograph ...

OPENALEX DOI: https://doi.org/10.7326/0003-4819-122-9-199505010-00007

Advancements in natural language processing: Implications, challenges, and future directions

Supriyono Supriyono, Aji Prasetya Wibawa, Suyono Suyono, Fachrul Kurniawan • Telematics and Informatics Reports (2024)

This research delves into the latest advancements in Natural Language Processing (NLP) and their broader implications, challenges, and future directions. With the ever-increasing volume of text data generated daily from diverse sources, ext...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.teler.2024.100173

Application of Convolutional Neural Network in Natural Language Processing

Wei Wang, Jianxun Gang • IEEE International Conference on Information Systems and Computer Aided Education (ICISCAE) (2018)

Convolutional neural network (Convolutionl Neural Network, CNN) is a multiple-layer neural network method to learn hierarchical characteristic of data. In recent years, CNN has developed rapidly in the design and calculation of natural lang...

OPENALEX DOI: https://doi.org/10.1109/iciscae.2018.8666928

Social network X and mental health in Brazil in times of coronavirus

Thallys da Silva Nogueira, Laisa Marcorela Andreoli Sarte, Priscila Vanessa Zabala Capriles Goliatt • HU Revista (2024)

Introduction: The COVID-19 pandemic has had a number of impacts on people's daily lives around the world. The radical change in people's daily routines has led to an increase in the use and consumption of social media content. The scenario ...

DOAJ Open Access (DOAJ) DOI: 10.34019/1982-8047.2024.v50.44375