1.433 hasil
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Journal of Big Data
Scopus
ISSN 2196-1115 · SpringerOpen · 1.433 artikel di indeks
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Artikel Jurnal
DeBERTa-based framework for detecting machine-generated content on social media: a comparative study
Abstract Machine-generated text, particularly deepfake content, presents substantial challenges for social media platforms. Detecting such content is crucial to maintaining trust and preventing misinformation. This study addresses the identification of machine-generated textual content on social…
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Artikel Jurnal
An integrated TQWT-deep learning framework for intelligent tool cutter selection using clonal selection and ant lion optimization
Abstract In precision manufacturing, the selection of cutting tools and uncontrolled tool wear is a major challenge which directly affects manufactured product quality, surface integrity and process efficiency. This work uses advanced deep learning (DL) architectures: InceptionNetv3, ResNeXt, and…
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Artikel Jurnal
Quantifying football player value: a novel combined rating and ML ensemble approach for predicting top players
Abstract In football (soccer), players are considered one of the most important elements of a club’s sporting and financial success. Therefore, it is extremely important to evaluate the (sporting) value and future potential of a player. Usually, scouts and other decision-makers are responsible for…
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Artikel Jurnal
Lowering barriers to federated learning: collaboration management and provenance
Abstract Federated learning (FL) is a promising paradigm for collaborative, privacy-preserving training of machine learning (ML) models on decentralized, private data. However, significant challenges limit the broader adoption of FL. First, existing FL workflows are often tailored to specific use…
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Artikel Jurnal
Novel transformer models for wheat disease classification with explainable insights
Abstract Wheat is one of the most critical staple crops globally and its productivity is severely threatened by various foliar diseases. These diseases leading to substantial economic and food security challenges. Accurate and early automated wheat disease classification is vital for reducing yield…
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Artikel Jurnal
Credit scoring modeling based on an improved two-stage method with fragmentary data
Abstract Credit scoring models play a significant role in risk management and decision-making processes within the credit industry. Nevertheless, these models often encounter challenges in dealing with fragmentary data characterized by missing values and varying patterns prevalent in credit…
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Artikel Jurnal
On mapping of topological structures and mathematical algorithms onto specialized architectures for graph-based computing
Abstract The first written mention of computing based on mapping of topological structures and mathematical algorithms onto graphs to be built into hardware, for graph-based computing, dates back to January 1984, when one of the authors of this text, as a Purdue University faculty member, submitted…
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Artikel Jurnal
Artificial Intelligence-driven privacy preservation in the internet of vehicles: a comprehensive systematic literature review
Abstract The rapid growth of the Internet of Vehicles (IoV) and the increasing use of Connected and Autonomous Vehicles (CAVs) are causing many privacy and security problems that traditional protection methods can not handle. IoV networks have a lot of different types of data flows, distributed…
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Artikel Jurnal
Machine learning insights into recommendation intention: evidence from the fitness industry
Abstract Recommendation intention, or the Net Promoter Score (NPS, in the terminology of fitness centers), is a tool that condenses into a single indicator the willingness of customers to recommend a service. It is important because it has become a widely used proxy for loyalty, brand advocacy, and…
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Artikel Jurnal
A secure and high-accuracy indoor positioning system using deep temporal fusion transformer and Galois field encryption
Abstract Indoor Positioning Systems (IPS) have garnered substantial interest due to their critical role in navigation, asset tracking, and security applications. However, conventional IPS technologies often face significant limitations in accuracy, security, and scalability, especially in dynamic…
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Artikel Jurnal
Enhancing satellite-based rainfall estimation in arid regions through AI-driven data fusion
Abstract Accurate precipitation estimation is crucial for hydrological modeling and water resource management, especially in arid and data-scarce regions like the UAE. This study presents an AI-driven data fusion framework to enhance satellite-based rainfall estimates by integrating three widely…
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Artikel Jurnal
Intelligent average utility pattern analysis using pre-large concept in dynamic stream data
Abstract Recent studies on high average utility pattern analysis aim to extract patterns from quantitative data considering the pattern length in incremental environments. However, traditional methods have the limitation that the pattern expansion process is conducted whenever incremental data…
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Artikel Jurnal
Building an effective chatbot for optimizing the debt collection process through large language models
Abstract Chatbots serve as a valuable tool for enhancing customer interactions. The traditional debt collection process is time-consuming and requires significant human effort. In this research, we have assessed the effectiveness of proposed chatbot systems in optimizing the debt collection…
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Artikel Jurnal
Fine-tuning topics through weighting aspect keywords
Abstract Organizations face growing challenges in deriving meaningful insights from vast amounts of specialized text data. Conventional topic modeling techniques are typically static and unsupervised, making them ill-suited for fast-evolving fields like quantum cryptography. These models lack…
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Artikel Jurnal
LongDocRank: graph-augmented large language models for unsupervised keyphrase extraction from long documents
Abstract Keyphrase extraction is a crucial NLP task that identifies key information from extensive text corpora, aiding in content summarization, search, and information retrieval. This paper presents LongDocRank, an advanced unsupervised keyphrase extraction framework that enhances large language…
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Artikel Jurnal
Multi-omics Mendelian randomization revealing SEMA7A as potential drug target for facial skin aging
Abstract Background The study of facial skin aging has attracted significant attention not only for its esthetic implications but also for its potential to shed light on the mechanisms underlying the development of age-related diseases. The purpose of this research was to systematically investigate…
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Artikel Jurnal
Integrated multiomics analysis and advanced machine learning techniques to refine molecular subtypes, stratify prognosis, characterize tumor microenvironment, and identify distinct sensitivity patterns to frontline therapies in lung squamous cell carcinoma
Abstract Lung squamous cell carcinoma (LUSC) is characterized by high aggressiveness and significant heterogeneity, currently lacking highly precise individualized treatment options. Leveraging computational methodologies, we integrated multi-omics data from LUSC patients using 10 clustering…
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Artikel Jurnal
Blockchain for e-healthcare: a review on secure data management frameworks and future challenges
Abstract The revolution in Blockchain Distributed Ledger Technology (BDLT) is changing conventional structures and creating previously unattainable opportunities across a variety of industrial fields. This study explores new developments, opportunities, and trends while tackling important issues…
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Artikel Jurnal
Multi-view graph representing interactive learning network for time series forecasting
Abstract Time series forecasting plays a vital role in domains such as energy consumption estimation, weather analysis, and traffic flow prediction, where accurate predictions are crucial for effective planning and decision-making. However, current methods often struggle to model complex…
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Artikel Jurnal
A review of machine learning with small and limited data
Abstract The abundance of large datasets has driven machine learning (ML) model performance and scalability breakthroughs. However, many domains and practical applications must contend with the limitations imposed by small and very small datasets. This survey thoroughly examines state-of-the-art…
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