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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

Applications of natural language processing and large language models in materials discovery

Xue Feng Jiang, Weiren Wang, Shaohan Tian, Hao Wang et al. • npj Computational Materials (2025)

The transformative impact of artificial intelligence (AI) technologies on materials science has revolutionized the study of materials problems. By leveraging well-characterized datasets derived from the scientific literature, AI-powered too...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1038/s41524-025-01554-0

BioBBC: a multi-feature model that enhances the detection of biomedical entities

Hind Alamro, Takashi Gojobori, Magbubah Essack, Xin Gao • Scientific Reports (2024)

Abstract The rapid increase in biomedical publications necessitates efficient systems to automatically handle Biomedical Named Entity Recognition (BioNER) tasks in unstructured text. However, accurately detecting biomedical entities is quit...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-024-58334-x

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

User‐Based Evaluation of Explainability Techniques for Misogyny Detection in Code‐Mixed Hindi–English

Sargam Yadav, Abhishek Kaushik, Kevin McDaid • Applied AI Letters (2026)

ABSTRACT Although artificial intelligence (AI) models have demonstrated great success and efficiency in automatically countering online hate speech and misogyny, they suffer from a lack of explainability and transparency. Explainable artifi...

DOAJ Open Access (DOAJ) DOI: 10.1002/ail2.70028

A Survey of the Application of Neural Networks to Event Extraction

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...

DOAJ Open Access (DOAJ) DOI: 10.26599/TST.2023.9010139

AI-generated draft replies to patient messages: exploring effects of implementation

Charlotte M. H. H. T. Bootsma-Robroeks, Charlotte M. H. H. T. Bootsma-Robroeks, Jessica D. Workum, Jessica D. Workum et al. • Frontiers in Digital Health (2025)

IntroductionThe integration of Large Language Models (LLMs) in Electronic Health Records (EHRs) has the potential to reduce administrative burden. Validating these tools in real-world clinical settings is essential for responsible implement...

DOAJ Open Access (DOAJ) DOI: 10.3389/fdgth.2025.1588143

Construction of a knowledge graph for the educational statistical indicator system based on large language models

WANG Pengyu, JIANG Shuming, WEI Zhiqiang, YU Jun, ZHANG Mengmeng • Shandong kexue (2026)

Current statistical work in the field of educational development faces challenges such as low knowledge-retrieval efficiency and high technical barriers to data utilization. This study focuses on the knowledge related to the indicator syste...

DOAJ Open Access (DOAJ) DOI: 10.3976/j.issn.1002-4026.2025079

A recurrent neural network framework for flexible and adaptive decision making based on sequence learning.

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...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pcbi.1008342

A systematic review of natural language processing applied to radiology reports

Arlene Casey, Emma Davidson, Michael Poon, Hang Dong et al. • BMC Medical Informatics and Decision Making (2021)

BACKGROUND: Natural language processing (NLP) has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology reports. Understanding recent developments in NLP application to r...

OPENALEX cc-by DOI: https://doi.org/10.1186/s12911-021-01533-7 PMC: 8176715

Natural Language Processing for Policymaking

Zhijing Jin, Rada F. Mihalcea • Springer eBooks (2022)

Abstract Language is the medium for many political activities, from campaigns to news reports. Natural language processing (NLP) uses computational tools to parse text into key information that is needed for policymaking. In this chapter, w...

OPENALEX cc-by DOI: https://doi.org/10.1007/978-3-031-16624-2_7

Quantum Algorithms for Compositional Natural Language Processing

William J. Zeng, Bob Coecke • Electronic Proceedings in Theoretical Computer Science (2016)

We propose a new application of quantum computing to the field of natural language processing. Ongoing work in this field attempts to incorporate grammatical structure into algorithms that compute meaning. In (Coecke, Sadrzadeh and Clark, 2...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.4204/eptcs.221.8

A comparative empirical evaluation of semantic clustering algorithms on static word embeddings

Asefeh Asemi, Rajab Kiani Shahvandy, Mahdi Houshangi • International Journal of Information Management Data Insights (2026)

Objective: This study conducts a comprehensive empirical evaluation of semantic clustering algorithms to identify the most effective approach for automatically organizing and extracting meaning from textual data. By systematically comparing...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jjimei.2026.100396

DEVELOPMENT OF A QUESTION ANSWERING CHATBOT FOR BLOCKCHAIN DOMAIN

Aigerim Mansurova, Aliya Nugumanova, Zhansaya Makhambetova • Scientific Journal of Astana IT University (2023)

Large Language Models (LLMs), such as ChatGPT, have transformed the field of natural language processing with their capacity for language comprehension and generation of human-like, fluent responses for many downstream tasks. Despite their ...

DOAJ Open Access (DOAJ) DOI: 10.37943/15XNDZ6667

Semantic Alignment in Disciplinary Tutoring System: Leveraging Sentence Transformer Technology

Rosana Abdoune, Lydia Lazib, Farida Dahmani-Bouarab, Nada Mimouni • Inteligencia Artificial (2024)

In this work, we present a disciplinary e-tutoring system that integrates ONTO-TDM, an ontology designed for teaching domain modeling, with advanced transformer technology. Our primary objective is to enhance semantic similarity tasks withi...

DOAJ Open Access (DOAJ)