A Comparative Study of Some Automatic Arabic Text Diacritization Systems by Ali Mijlad, Yacine El Younoussi

“…This task, when automated, shows better results for some natural language processing tasks; hence, it is necessary for the field of Arabic language processing. …”
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COVID-19 Infodemic in Malaysia: Conceptualizing Fake News for Detection by Chee Kuan Lim, Zurinahni Zainol, Bahiyah Omar, Noor Farizah Ibrahim

“…Under the study of COVID-19 fake news detection, the synthetic minority oversampling technique (SMOTE) is used to generate synthetic instances of real news in the training set after natural language processing (NLP) and before data modelling because the number of fake news is approximately three times greater than that of real news. …”
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LEXCONN: A French Lexicon of Discourse Connectives by Charlotte Roze, Laurence Danlos, Philippe Muller

“…While a lexicon of discourse connectives associated with the relations they express can be very useful for researchers, especially in Natural Language Processing, few projects aim at collecting them exhaustively, and only in a small number of languages. …”
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Klasifikasi Laporan Keluhan Pelayanan Publik Berdasarkan Instansi Menggunakan Metode LDA-SVM by Muhammad Alkaff, Andreyan Rizky Baskara, Irham Maulani

“…Therefore, we need a solution that can automatically determine the report's context using Natural Language Processing techniques. This study aims to build automatic report classifications based on report topics addressed to authorized agencies by combining Latent Dirichlet Allocation (LDA) and Support Vector Machine (SVM). …”
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Teknik Identifikasi Fitur Berdasarkan Kalimat Pernyataan Kebutuhan dalam Konteks Pengembangan Software Product Line by M Syauqi Haris, Tri Astoto Kurniawan

“…The pattern of writing a requirement sentence with boilerplate requirements is used as the basis for automatically identifying software features using natural language processing (NLP) tools. In this research, 4 (four) dependency parser rules are proposed, which is one of the pipelines in NLP. …”
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Co-producing a safe mobility and falls informatics platform to drive meaningful quality improvement in the hospital setting: a mixed-methods protocol for the insightFall study by Ben Glampson, Clare Leon-Villapalos, Erik Mayer, Rachael Lear, Phoebe Averill, Catalina Carenzo, Rachel Tao, Robert Latchford

“…Based on these initial insights and further consultation with lay partners and clinical staff, a final data extraction template will be agreed. Natural language processing pipelines will be co-produced, clinically validated and integrated with QlikView. …”
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RespiroDynamics: A Multifaceted Dataset for Enhanced Lung Health Assessment Using Deep Learning by Ahmed Sharshar, Muhammad Sharshar, Hosam Elhady, Ahmed Aboeitta, Youssef Nafea, Yasser Ashraf, Mohammad Yaqub, Mohsen Guizani

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Joint Distribution pada Weighted Majority Vote (WMV) untuk Peningkatan Kinerja Sentiment Analysis Tersupervisi pada Dataset Twitter by Bagus Setya Rintyarna

“…Sentiment analysis adalah teknik komputasi text mining berbasis natural language processing (NLP) untuk mengekstraksi pendapat seseorang yang diungkapkan dalam platform online, termasuk dalam platform microblogging Twitter, salah satu platform microblogging yang paling popular digunakan di Indonesia. …”
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Relieve Adversarial Attacks Based on Multimodal Training by Lai Hongjie

“…Deep learning models have reached great success in many areas such as image recognition and natural language processing. But their robustness has always been a concern. …”
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An Empirical Configuration Study of a Common Document Clustering Pipeline by Anton Eklund, Mona Forsman, Frank Drewes

“… Document clustering is frequently used in applications of natural language processing, e.g. to classify news articles or creating topic models. …”
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Digital humanities approaches to analyzing indonesian language texts as non-western languages by Rastya Mutiarani Zahra

“…The primary objective is to develop tailored digital humanities methodologies, applying computational tools such as text mining, natural language processing, and corpus linguistics to analyze linguistic and thematic patterns within Indonesian texts. …”
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THE REVIEW OF MECHANICAL FAULT DIAGNOSIS METHODS BASED ON CONVOLUTIONAL NEURAL NETWORK by WU DingHai, REN GuoQuan, WANG HuaiGuang, ZHANG YunQiang

“…The Convolutional Neural Network（ CNN） is a classic structure of deep learing and which is being widely and successfully used in the fields of computer vision,target detection,natural language processing,and speech recognition. Based on a detailed analysis of the current status and needs of mechanical system fault diagnosis,this paper introduces the structure of CNN,and summarizes the application of CNN in the field of mechanical faults from the aspects of input data type,network structure design and migration learning. …”
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6G knowledge system construction: academic knowledge mining and on-demand application for full domains and omni scenarios by Zifan SHA, Nan CHENG, Yilong HUI, Wenwei YUE, Yuchuan FU, Ruijin SUN

“…At present, the concepts related to 6G have not been unified, and there is an urgent need for consistent cognition and definition.Academics and industries lack a clear understanding of the overall development of 6G and the research progress in related fields.Therefore, the 6G knowledge base and knowledge system was constructed.Firstly, the existing 6G academic documents were automatically screened and stored in a structured way.Secondly, a 6G knowledge base was constructed on the basis of labeling and standardizing text data.In addition, a comprehensive statistical analysis was conducted across all domains of 6G based on the knowledge base and the technologies such as natural language processing, deep neural network and latent tree model were used to realize the extraction and generation of 6G knowledge.Finally, on the basis of large-scale model training, the on-demand knowledge application was realized for diversified service requirements.…”
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Machine learning in medicine: what clinicians should know by Jordan Zheng Ting Sim, Qi Wei Fong, Weimin Huang, Cher Heng Tan

“…Herein, we introduce basic concepts and terms used in AI and ML, and aim to demystify commonly used AI/ML algorithms such as learning methods including neural networks/deep learning, decision tree and application domain in computer vision and natural language processing through specific examples. We discuss how machines are already being used to augment the physician’s decision-making process, and postulate the potential impact of ML on medical practice and medical research based on its current capabilities and known limitations. …”
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Improved Convolutional Neural Image Recognition Algorithm based on LeNet-5 by Lijie Zhou, Weihai Yu

“…Fruitful results have been achieved in image recognition, speech recognition, and natural language processing. Compared with traditional neural network, convolutional weight sharing, sparse connection, and pooling operations in convolutional neural network greatly reduce the number of training parameters, reduce size of feature map, simplify network model, and improve training efficiency. …”
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Code vulnerability detection method based on graph neural network by Hao CHEN, Ping YI

“…The schemes of using neural networks for vulnerability detection are mostly based on traditional natural language processing ideas, processing the code as array samples and ignoring the structural features in the code, which may omit possible vulnerabilities.A code vulnerability detection method based on graph neural network was proposed, which realized function-level code vulnerability detection through the control flow graph feature of the intermediate language.Firstly, the source code was compiled into an intermediate representation, and then the control flow graph containing structural information was extracted.At the same time, the word vector embedding algorithm was used to initialize the vector of basic block to extract the code semantic information.Then both of above were spliced to generate the graph structure sample data.The multilayer graph neural network model was trained and tested on graph structure data features.The open source vulnerability sample data set was used to generate test data to evaluate the method proposed.The results show that the method effectively improves the vulnerability detection ability.…”
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PENERAPAN ARTIFICIAL INTELLIGENCE (AI) DALAM PERAMALAN AKUNTANSI TINJAUAN LITERATUR DAN AGENDA PENELITIAN MASA DEPAN by Gilang Surya Pratama, Agus Munandar

“…The analysis results show significant improvements in forecasting accuracy using AI technology, with Machine Learning achieving 78% accuracy in revenue forecasting, Deep Learning 85% in financial trend prediction, and Natural Language Processing 89% in sentiment analysis. Major implementation challenges include data quality, infrastructure limitations, and data security. …”
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Research on Sarcastic Emotion Recognition Based on Multiple Feature Fusion by Si Kaihao

“…Sarcasm detection significantly enhances the performance of various natural language processing applications, such as sentiment analysis, opinion mining, and stance detection. …”
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Artificial Intelligence (AI)-driven approach to climate action and sustainable development by Haein Cho, Emmanuel Ackom

“…An Artificial Intelligence (AI)-based approach is proposed in this study to explore the interconnectedness by applying machine learning classifier and natural language processing. Middle- and low-income countries with high emissions tend to have low NDC targets and contain similar information in VNR reports. …”
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À la recherche des haïdouks. Annoter les entités spatiales dans des romans roumains du xixe siècle by Ioana Galleron, Roxana Patraș, Camelia Grădinaru, Frédérique Mélanie-Becquet

“…To verify if this different vision reverberates in novels, the aim was to collect all nominal and adverbial phrases referring to space, thus going largely beyond toponyms, that are usually marked-up and examined in digital humanities and natural language processing projects. After a presentation of the main differences between our approach and those prevailing in older or more recent studies in spatial literary analyses, we focus on the elaboration of the annotation scheme and comment upon the results of the inter-annotator agreement, as measured on a set of ten fully-annotated samples, of a thousand words each, from our novels.…”
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