Dual-channel knowledge attention for traditional Chinese medicine syndrome differentiation by Boting Liu, Hengqiu Huang, Xiaoman Liu, Juntao Zhao, Jiean Mo

“…Abstract With the rapid advancement of Natural Language Processing (NLP) technologies, the application of NLP to enable intelligent syndrome differentiation in Traditional Chinese Medicine (TCM) has become a popular research focus. …”
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Detecting sarcasm in user-generated content integrating transformers and gated graph neural networks by Zhenkai Qin, Qining Luo, Zhidong Zang, Hongpeng Fu

“…Sarcasm often expresses negative emotions through seemingly positive or exaggerated language, making its detection a complex task in natural language processing. To address this issue, the present study proposes a novel sarcasm detection model that combines bidirectional encoder representations from transformers (BERT) with gated graph neural networks (GGNN), further enhanced by a self-attention mechanism to more effectively capture ironic cues. …”
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Linguistic biomarkers of dementia in Italian patients living in Lombardy: insights from NLP analysis by Maria Letizia Piccini Bianchessi, Gloria Gagliardi

“…The new frontier in the analysis of spoken language productions is the employment of Natural Language Processing (NLP) techniques and Artificial Intelligence (AI), as they enable an ecological and non-intrusive detection of dementia. …”
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A deep learning framework for gender sensitive speech emotion recognition based on MFCC feature selection and SHAP analysis by Qingqing Hu, Yiran Peng, Zhong Zheng

“…Abstract Speech is one of the most efficient methods of communication among humans, inspiring advancements in machine speech processing under Natural Language Processing (NLP). This field aims to enable computers to analyze, comprehend, and generate human language naturally. …”
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A hybrid extraction model for semantic knowledge discovery of water conservancy big data by Yanna Feng, Feng Zhang, Yongheng Zhang, Jiangang Dong, PengJu Wang

“…To address the growing demand for efficient public opinion analysis in water conservancy and related domains, as well as the inefficiencies and limited scalability of existing automated web data extraction algorithms for multi-source datasets, this research integrates advanced technologies including big data analytics, natural language processing, and deep learning. A novel, transferable web information extraction model based on deep learning (WIEM-DL) is proposed, leveraging knowledge graphs, machine learning, and ontology-based methods. …”
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Virtual Electroencephalogram Acquisition: A Review on Electroencephalogram Generative Methods by Zhishui You, Yuzhu Guo, Xiulei Zhang, Yifan Zhao

“…Taking inspiration from the resounding success of generative models in computer vision and natural language processing arenas, the generation of synthetic EEG data from limited recorded samples has recently garnered burgeoning attention. …”
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Empowering medical systematic reviews with large language models: methods, development directions, and applications by Yannan HUANG, Haoran SANG, Yu LIU, Liantao MA, Yinghao ZHU

“…In recent years, large language models (LLMs), exemplified by ChatGPT and DeepSeek, have demonstrated significant potential in supporting medical systematic reviews due to their powerful natural language processing capabilities. However, its inherent challenges such as the"hallucination"problem and lagging knowledge update limit the reliability of its direct application. …”
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Transformer-Based Model for Monocular Visual Odometry: A Video Understanding Approach by Andre O. Francani, Marcos R. O. A. Maximo

“…Transformer-based architectures have dominated the state-of-the-art in natural language processing and computer vision tasks, such as image and video understanding. …”
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Detecting hate in diversity: a survey of multilingual code-mixed image and video analysis by Hafiz Muhammad Raza Ur Rehman, Mahpara Saleem, Muhammad Zeeshan Jhandir, Eduardo Silva Alvarado, Helena Garay, Imran Ashraf

“…We fill research gaps by assessing a variety of methods, including deep learning, machine learning, and natural language processing, especially for complicated data like code-mixed and cross-lingual text. …”
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AI and Creativity in Entrepreneurship Education: A Systematic Review of LLM Applications by Jeong-Hyun Park, Seon-Joo Kim, Sung-Tae Lee

“…Large Language Models (LLMs) provide personalized learning experiences through natural language processing (NLP), enhancing real-time feedback and problem-solving skills. …”
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A Dual-Enhanced Hierarchical Alignment Framework for Multimodal Named Entity Recognition by Jian Wang, Yanan Zhou, Qi He, Wenbo Zhang

“…Multimodal amed entity recognition (MNER) is a natural language-processing technique that integrates text and visual modalities to detect and segment entity boundaries and their types from unstructured multimodal data. …”
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Translanguaging und sein Potenzial für den DaF-Unterricht sowie fachsprachlichen DaF-Unterricht by Saša Jazbec

“…This paper focuses on translanguaging, a new approach to language processing and use that starts with the individual and their single linguistic repertoire.  …”
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Artificial intelligence in the tourism business: a systematic review by Alexandra Lorena López-Naranjo, Mariana Isabel Puente-Riofrio, Verónica Adriana Carrasco-Salazar, Juan Diego Erazo-Rodríguez, Pamela Alexandra Buñay-Guisñan

“…The main findings indicate that, in the tourism industry, the most commonly used AI technologies include Natural Language Processing (NLP) and deep learning with Neural Networks, with chatbots and models such as CNNs and LSTMs being particularly prominent. …”
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Advanced Applications of Artificial Intelligence in Pharmacovigilance: Current Trends and Future Perspectives by Yogesh S Ahire, Jayesh H Patil, Harshita N Chordiya, Rashmi A Deore, Vinod A Bairagi

“…They are adept at applying sophisticated algorithms, machine learning models, and natural language processing to glean insights from unstructured data sources like clinical notes, patient narratives, and regulatory reports. …”
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Large language models prompt engineering as a method for embodied cognitive linguistic representation: a case study of political metaphors in Trump’s discourse by Haohan Meng, Xiaoyu Li, Jinhua Sun

“…Future research will focus on optimizing these models, conducting comparative analyses with traditional methods, and exploring their applicability in cross-cultural contexts, with the goal of providing more precise and effective tools for both natural language processing (NLP) and political linguistics research.…”
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Digital Transformation in Aftersales and Warranty Management: A Review of Advanced Technologies in I4.0 by Vicente González-Prida, Carlos Parra Márquez, Pablo Viveros Gunckel, Fredy Kristjanpoller Rodríguez, Adolfo Crespo Márquez

“…Based on an already established eight-phase framework for warranty management, this paper reviews machine learning (ML), natural language processing (NLP), and predictive analytics, among other advanced technologies, to enhance warranty optimization processes. …”
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Utility analysis and demonstration of real-world clinical texts: A case study on Japanese cancer-related EHRs. by Shuntaro Yada, Tomohiro Nishiyama, Shoko Wakamiya, Yoshimasa Kawazoe, Shungo Imai, Satoko Hori, Eiji Aramaki

“…We evaluated the information gained by supplementing structured data with clinical concepts extracted from unstructured text by leveraging natural language processing techniques. Using a machine learning-based pretrained named entity recognition tool, we extracted disease and medication names from real discharge summaries in a Japanese hospital and linked them to medical concepts using medical term dictionaries. …”
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Delayed redevelopment in urban expansion: opportunities for the preservation and revitalisation of collective memory in Shiqiao Town, Chengdu by Shenghui Tang, Qian Guo

“…Via participant observations, semistructured interviews, netnography, natural language processing, and policy content reviews, this paper investigated collective memories based on the everyday lives and public perceptions of residents, with the aim of facilitating interactions between social groups, historic districts, and the city. …”
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Exploiting Contextual Word Embedding of Authorship and Title of Articles for Discovering Citation Intent Classification by Muhammad Roman, Abdul Shahid, Muhammad Irfan Uddin, Qiaozhi Hua, Shazia Maqsood

“…Text information can contribute well if new natural language processing techniques are applied to capture the context of text data. …”
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A Knowledge-Driven Approach to Automate Job Hazard Analysis Process by Sonali Pandithawatta, Raufdeen Rameezdeen, Seungjun Ahn, Christopher W. K. Chow, Nima Gorjian

“…The data were imported to the JHAKG from an incident database using rule-based natural language processing (NLP) which helped to extract implicit information not evident in the traditional JHA document. …”
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