A Client-Centric Evaluation System to Evaluate Guest’s Satisfaction on Airbnb Using Machine Learning and NLP by Mohamed Chiny, Omar Bencharef, Moulay Youssef Hadi, Younes Chihab

“…So, we applied natural language processing (NLP) algorithms to the reviews in order to find clues that could help us segment them, and then we trained two regression models, multiple linear regression and support vector regression, in order to calculate the coefficients acting on each of the 6 elementary scores (precision, cleanliness, check-in, communication, location, and value) noted on Airbnb, taking into account the category of customers who evaluated the performance of their accommodation. …”
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Climate adaptation plans and “green jobs”: challenges for implementing a responsive, multi-skilled workforce in Worcester, Massachusetts by Varun Bhat, Sarah Strauss

“…We conduct this analysis with the help of natural language processing and qualitative coding in the City of Worcester, Massachusetts, USA using job data from Indeed and semi-structured interviews. …”
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SynoExtractor: A Novel Pipeline for Arabic Synonym Extraction Using Word2Vec Word Embeddings by Rawan N. Al-Matham, Hend S. Al-Khalifa

“…Automatic synonym extraction plays an important role in many natural language processing systems, such as those involving information retrieval and question answering. …”
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Screening of multi deep learning-based de novo molecular generation models and their application for specific target molecular generation by Yishu Wang, Mengyao Guo, Xiaomin Chen, Dongmei Ai

“…In particular, the emergence of a novel natural language processing (NLP) architecture called the transformer has improved the state-of-the-art performance of existing AI technologies. …”
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T-LLaMA: a Tibetan large language model based on LLaMA2 by Hui Lv, Chi Pu, La Duo, Yan Li, Qingguo Zhou, Jun Shen

“…To our knowledge, T-LLaMA stands as the first large-scale language model in Tibetan natural language processing (NLP) with parameters in the billion range. …”
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Deteksi Cyberbullying dengan Mesin Pembelajaran Klasifikasi (Supervised Learning): Peluang dan Tantangan by Yudi Setiawan, Nur Ulfa Maulidevi, Kridanto Surendro

“…Penelitian deteksi pola dan karakteristik cyberbullying banyak dilakukan dengan berbagai metode, seperti dengan mengimplementasikan Machine Learning, Natural Language Processing (NLP), dan Sentiment Analysis yang memiliki variasi akurasi yang berbeda, dengan keunggulan dan kelemahan dari masing-masing metode. …”
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Recognition model for major depressive disorder in Arabic user-generated content by Esraa M. Rabie, Atef F. Hashem, Fahad Kamal Alsheref

“…This research offers a novel framework for depression detection from Arabic textual data utilizing deep learning (DL), natural language processing (NLP), machine learning (ML), and BERT transformers techniques in light of the disease’s high prevalence. …”
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One size fits all: Enhanced zero-shot text classification for patient listening on social media by Veton Matoshi, Maria Carmela De Vuono, Roberto Gaspari, Mark Kröll, Michael Jantscher, Sara Lucia Nicolardi, Giuseppe Mazzola, Manuela Rauch, Vedran Sabol, Eileen Salhofer, Riccardo Mariani

“…Recent advancements in Artificial Intelligence (AI), especially in Natural Language Processing (NLP), have enabled the analysis of vast social media datasets, also called Social Media Listening (SML), providing insights not only into patient perspectives but also into those of other interest groups such as caregivers. …”
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Attention-based interactive multi-level feature fusion for named entity recognition by Yiwu Xu, Yun Chen

“…Abstract Named Entity Recognition (NER) is an essential component of numerous Natural Language Processing (NLP) systems, with the aim of identifying and classifying entities that have specific meanings in raw text, such as person (PER), location (LOC), and organization (ORG). …”
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DeepSeek vs. ChatGPT: Comparative Efficacy in Reasoning for Adults’ Second Language Acquisition Analysis by Mohammad Mahyoob Albuhairy, Jeehaan Algaraady

“…The advent of new generation language models has revolutionized the field of natural language processing (NLP) due to their exceptional understanding and human language generation capabilities. …”
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Decoding substance use disorder severity from clinical notes using a large language model by Maria Mahbub, Gregory M. Dams, Sudarshan Srinivasan, Caitlin Rizy, Ioana Danciu, Jodie Trafton, Kathryn Knight

“…Traditional natural language processing (NLP) methods face limitations in accurately parsing such diverse clinical language. …”
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How much can we save by applying artificial intelligence in evidence synthesis? Results from a pragmatic review to quantify workload efficiencies and cost savings by Seye Abogunrin, Jeffrey M. Muir, Clarissa Zerbini, Grammati Sarri

“…Data on efficiencies (time- and cost-related) were collected.ResultsWe identified 25 eligible studies: 13 used machine learning, 10 used natural language processing, and once each used a systematic review automation tool and a non-specified AI tool. …”
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A comprehensive dataset and neural network approach for named entity recognition in the Uzbek languageMendeley Data by Davlatyor Mengliev, Vladimir Barakhnin, Mukhriddin Eshkulov, Bahodir Ibragimov, Shohrux Madirimov

“…The proposed dataset and trained model contribute to the development of natural language processing in the Uzbek language. In addition, the authors also conducted an analysis of existing works, as well as a comparative analysis, which will help to identify the distinctive features and novelty of the proposed work. …”
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TIBW: Task-Independent Backdoor Watermarking with Fine-Tuning Resilience for Pre-Trained Language Models by Weichuan Mo, Kongyang Chen, Yatie Xiao

“…Pre-trained language models such as BERT, GPT-3, and T5 have made significant advancements in natural language processing (NLP). However, their widespread adoption raises concerns about intellectual property (IP) protection, as unauthorized use can undermine innovation. …”
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A machine learning decision support tool optimizes WGS utilization in a neonatal intensive care unit by Edwin F. Juarez, Bennet Peterson, Erica Sanford Kobayashi, Sheldon Gilmer, Laura E. Tobin, Brandan Schultz, Jerica Lenberg, Jeanne Carroll, Shiyu Bai-Tong, Nathaly M. Sweeney, Curtis Beebe, Lawrence Stewart, Lauren Olsen, Julie Reinke, Elizabeth A. Kiernan, Rebecca Reimers, Kristen Wigby, Chris Tackaberry, Mark Yandell, Charlotte Hobbs, Matthew N. Bainbridge

“…Abstract The Mendelian Phenotype Search Engine (MPSE), a clinical decision support tool using Natural Language Processing and Machine Learning, helped neonatologists expedite decisions to whole genome sequencing (WGS) to diagnose patients in the neonatal intensive care unit. …”
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Predicting accrual success for better clinical trial resource allocation by Sisi Ma, Yinzhao Wang, John Wagner, Steve Johnson, Serguei Pakhomov, Constantin Aliferis

“…Features of the dataset were informed by prior literature and constructed using data-driven natural language processing methods. We built predictive models for accrual failure using state-of-the-art supervised machine learning protocols and methods. …”
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Hate Speech Detection Using Large Language Models: A Comprehensive Review by Aish Albladi, Minarul Islam, Amit Das, Maryam Bigonah, Zheng Zhang, Fatemeh Jamshidi, Mostafa Rahgouy, Nilanjana Raychawdhary, Daniela Marghitu, Cheryl Seals

“…We analyze the evolution of LLMs in natural language processing and examine their strengths and limitations in identifying hate speech. …”
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CTHP: Selection for adoption of open‐source bioinformatics software based on a customised ISO 25010 quality model, three‐way decision and Delphi hierarchy process by Yuqi Li, Yixin Bian, Ziheng Zhang, Song Zhao, Yiqi Liu

“…Finally, as a case study, the proposed approach is applied to assist the decision‐making process of two popular natural language processing frameworks in the Bioinformatics area. …”
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The Utility of ChatGPT in Educational Research—Potential Opportunities and Pitfalls by Turgut Karakose

“…Background/purpose –Leveraging the latest developments in natural language processing, recent versions of ChatGPT has demonstrated astounding performance on a wide array of tasks through its ability to understand and generate human language, and respond to diverse conversational prompts. …”
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A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity by Abdullah Al Siam, Moutaz Alazab, Albara Awajan, Nuruzzaman Faruqui

“…We examine cutting-edge AI methodologies and principal models across many domains, including machine learning algorithms, deep learning architectures, natural language processing techniques, and anomaly detection algorithms, emphasizing their distinct contributions to enhancing security. …”
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