Risultati della ricerca - language learning algorithm
-
21
Personal Data Recognition Using a Deep Learning Model
Pubblicazione 2024-03-01“...In this paper, deep learning models featuring different neural network architectures were implemented and compared against rule-based algorithms. ...”Protecting personal identifiable information is a crucial issue today due to individuals leaving traces of their activities on social media and various digital platforms, which can be exploited by attackers for identity theft and fraud. Consequently, there is a need to develop effective methods for...
Testo
Articolo -
22
Machine Learning in the National Economy
Pubblicazione 2025-07-01“...The main methods include an analysis of scientific literature, statistical data analysis, modeling using machine learning algorithms, and practical implementation of economic models with programming languages such as Python and machine learning libraries.To analyze economic data, methods such as linear regression, decision trees, and neural networks were selected, as they effectively predict changes in key macroeconomic indexes such as GDP, inflation, exchange rates, and unemployment levels. ...”This article examines the application of machine learning in the national economy. It describes the main concepts and methods of machine learning, including supervised, unsupervised, and reinforcement learning. Key areas of using this technology in the economy are analyzed, such as market trend fore...
Testo
Articolo -
23
An Empirical Comparison of Machine Learning and Deep Learning Models for Automated Fake News Detection
Pubblicazione 2025-06-01“...In this study, we systematically evaluate the mathematical foundations and empirical performance of five representative models for automated fake news classification: three classical machine learning algorithms (Logistic Regression, Random Forest, and Light Gradient Boosting Machine) and two state-of-the-art deep learning architectures (A Lite Bidirectional Encoder Representations from Transformers—ALBERT and Gated Recurrent Units—GRUs). ...”Detecting fake news is a critical challenge in natural language processing (NLP), demanding solutions that balance accuracy, interpretability, and computational efficiency. Despite advances in NLP, systematic empirical benchmarks that directly compare both classical and deep models—across varying in...
Testo
Articolo -
24
Privacy-Aware Detection for Large Language Models Using a Hybrid BiLSTM-HMM Approach
Pubblicazione 2025-01-01“...Large Language Models (LLMs) have transformed natural language processing, enabling applications such as conversational agents and machine translation. ...”Large Language Models (LLMs) have transformed natural language processing, enabling applications such as conversational agents and machine translation. However, their deployment introduces significant privacy concerns, including the memorization and unintended disclosure of sensitive data. Existing...
Testo
Articolo -
25
Detecting of a Patient's Condition From Clinical Narratives Using Natural Language Representation
Pubblicazione 2022-01-01“...<italic>Conclusions:</italic> This study successfully applied learning representation and machine learning algorithms to detect heart failure in a single French institution from clinical natural language. ...”The rapid progress in clinical data management systems and artificial intelligence approaches enable the era of personalized medicine. Intensive care units (ICUs) are ideal clinical research environments for such development because they collect many clinical data and are highly computerized. <it...
Testo
Articolo -
26
The Integration Of Artificial Intelligence In English Language Teaching And Machine Translation: A Bridge Between Theory And Practice In Language Teaching For Specific Purposes.
Pubblicazione 2025-05-01“... Integrating AI into ELT and machine translation marks a major advancement, particularly in the teaching of languages for specific purposes (LSP). This field is crucial in a globalized context, where proficiency in foreign languages and specialized communication is essential. ...”Integrating AI into ELT and machine translation marks a major advancement, particularly in the teaching of languages for specific purposes (LSP). This field is crucial in a globalized context, where proficiency in foreign languages and specialized communication is essential. This study explores how...
Testo
Articolo -
27
Species Differences of Imperative Mood of Russian Verbs in the Linguodidactic Aspect
Pubblicazione 2018-08-01Soggetti: TestoOne of the most difficult topics to be learned by students of Russian as a foreign language is represented by the verb aspects at the imperative mood. In this paper, the authors underline the need to develop a new approach to explain the differences and the correct use of imperative aspects used at...
Articolo -
28
Hybrid Feature and Optimized Deep Learning Model Fusion for Detecting Hateful Arabic Content
Pubblicazione 2025-01-01TestoDetecting hate speech in Arabic social media content is critical for ensuring safe, inclusive, and respectful online communication. However, this task remains challenging due to Arabic’s morphological richness, dialectal variations such as Levantine, and the scarcity of high-quality annot...
Articolo -
29
An annotated morphological dataset for Uzbek word forms: Towards rule-based and machine learning approachesMendeley Data
Pubblicazione 2025-08-01“...This research paper presents a morphologically annotated dataset for the Uzbek language, specifically designed for morphological analysis algorithms. ...”This research paper presents a morphologically annotated dataset for the Uzbek language, specifically designed for morphological analysis algorithms. The dataset contains 3022 manually annotated word forms, each annotated with root, affix, and part-of-speech information. Two morphological analysis a...
Testo
Articolo -
30
A Weighted Voting Approach for Traditional Chinese Medicine Formula Classification Using Large Language Models: Algorithm Development and Validation Study
Pubblicazione 2025-07-01TestoAbstract BackgroundSeveral clinical cases and experiments have demonstrated the effectiveness of traditional Chinese medicine (TCM) formulas in treating and preventing diseases. These formulas contain critical information about their ingredients, efficacy, and indications. Cla...
Articolo -
31
Harnessing Moderate-Sized Language Models for Reliable Patient Data Deidentification in Emergency Department Records: Algorithm Development, Validation, and Implementation Study
Pubblicazione 2025-04-01“...ObjectiveThe objective of our study is to design, implement, and evaluate deidentification algorithms using fine-tuned moderate-sized open-source language models, ensuring their suitability for production inference tasks on personal computers. ...”Abstract BackgroundThe digitization of health care, facilitated by the adoption of electronic health records systems, has revolutionized data-driven medical research and patient care. While this digital transformation offers substantial benefits in health care efficiency and a...
Testo
Articolo -
32
Extracting Knowledge From Scientific Texts on Patient-Derived Cancer Models Using Large Language Models: Algorithm Development and Validation Study
Pubblicazione 2025-06-01TestoAbstract BackgroundPatient-derived cancer models (PDCMs) have become essential tools in cancer research and preclinical studies. Consequently, the number of publications on PDCMs has increased significantly over the past decade. Advances in artificial intelligence, particularl...
Articolo -
33
Reproductive method in teaching Russian to foreign students and its innovative aspects
Pubblicazione 2021-06-01Soggetti: TestoThe reproductive method in the system of teaching Russian as a foreign language is aimed at reproducing the ways of activity by foreign students according to the algorithms presented by the teacher, at enriching them with knowledge, skills and abilities, as well as at forming the main mental operati...
Articolo -
34
Predictive diagnostics of computer systems logs using natural language processing techniques
Pubblicazione 2025-07-01“...The proposed approach is based on semisupervised learning combined with natural language processing techniques. ...”This study aims to develop and validate a method for predictive diagnostics and anomaly detection in computer system logs, using the Vertica database as a case study. The proposed approach is based on semisupervised learning combined with natural language processing techniques. A specialized parser...
Testo
Articolo -
35
Using explainable machine learning and eye-tracking for diagnosing autism spectrum and developmental language disorders in social attention tasks
Pubblicazione 2025-06-01“...Two key challenges must be addressed: the difficulty in reliably distinguishing between disorders with overlapping features, and the efficient management of eye-tracking data to yield clinically meaningful outcomes.PurposeThe aim of this study is to apply explainable machine learning (XML) algorithms to eye-tracking data from social attention tasks involving children with ASD, developmental language disorder (DLD), and typical development (TD), in order to assess classification accuracy and identify the variables that best differentiate between groups.MethodsNinety-three children participated in a visual preference task that paired social and non-social stimuli, specifically designed to capture features characteristic of ASD. ...”BackgroundEye-tracking technology has proven to be a valuable tool in detecting visual scanning patterns associated with autism spectrum disorder (ASD). Its advantages in easily obtaining reliable measures of social attention could help overcome many of the current challenges in the assessment of ne...
Testo
Articolo -
36
Research on knowledge concept extraction method based on few-shot learning and chain-of-thought prompting
Pubblicazione 2025-01-01“...In view of the above challenges, a method based on few-shot learning and chain-of-thought prompting for knowledge concept extraction was proposed, utilizing open-source large language models. ...”Knowledge concept extraction has important application value in the fields of education, medical care, and finance. Knowledge concept extraction is a sub-task of named entity recognition. However, due to the lack of data sets and the particularity of knowledge concept entity types, directly applying...
Testo
Articolo -
37
Data Collection for Automatic Depression Identification in Spanish Speakers Using Deep Learning Algorithms: Protocol for a Case-Control Study
Pubblicazione 2025-07-01TestoBackgroundDepression is a mental health condition that affects millions of people worldwide. Although common, it remains difficult to diagnose due to its heterogeneous symptomatology. Mental health questionnaires are currently the most used assessment method to screen depress...
Articolo -
38
An Innovative Approach for Fake News Detection using Machine Learning
Pubblicazione 2023-06-01TestoThis research aims to increase people's awareness of fake news on online social networks and help them determine the reliability of information they consume. It investigates methods for detecting fake news sources, authors, and subjects on online social networks. The project uses an open-sourc...
Articolo -
39
Attention-based hybrid deep learning model with CSFOA optimization and G-TverskyUNet3+ for Arabic sign language recognition
Pubblicazione 2025-06-01“...This model uses a newly introduced G-TverskyUNet3+ to detect regions of interest in preprocessed Arabic sign language images. In addition, employing a novel metaheuristic algorithm, the Crisscross Seed Forest Optimization Algorithm, which combines the Crisscross Optimization and Forest Optimization algorithms to determine the best features from the extracted texture, color, and deep learning features. ...”Abstract Arabic sign language (ArSL) is a visual-manual language which facilitates communication among Deaf people in the Arabic-speaking nations. Recognizing the ArSL is crucial due to variety of reasons, including its impact on the Deaf populace, education, healthcare, and society, as well. Previo...
Testo
Articolo -
40
Synergizing Intelligence and Privacy: A Review of Integrating Internet of Things, Large Language Models, and Federated Learning in Advanced Networked Systems
Pubblicazione 2025-06-01TestoBringing together the Internet of Things (IoT), LLMs, and Federated Learning (FL) offers exciting possibilities, creating a synergy to build smarter, privacy-preserving distributed systems. This review explores the merging of these technologies, particularly within edge computing environments. We ex...
Articolo