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Big Data Mining and Analytics
Scopus
ISSN 2096-0654 · Tsinghua University Press · 414 artikel di indeks
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Artikel Jurnal
DPRP: A Lightweight and Scalable Multi-Layer Blockchain Based on Swarm Reputation for Trustworthy AIoT Collaboration
Artificial Intelligence of Things (AIoT)-enabled Edge Collaboration systems (AEC) are characterized by openness, heterogeneity, and constrained device resources, which pose severe challenges to achieving trusted collaboration within AEC. While blockchain provides a trusted foundation for…
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Artikel Jurnal
Graph-Based Multimodal Fusion Framework with Correlation-Aware Learning for Alzheimer’s Disease Prediction
Accurate diagnosis of Alzheimer’s Disease (AD) is essential for early intervention. Traditional methods relying on single-modality data often fail to capture the complexity of the disease, limiting diagnostic accuracy. Integrating multimodal data, such as structural Magnetic Resonance Imaging…
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Artikel Jurnal
HOSVD++: A Tensor-Based High Order SVD++ Recommendation System
In the context of big data enabling e-commerce, content platforms, and social networks, Recommendation Systems (RSs) play a crucial role in providing personalized items and services suggestions to users. Among the various RSs approaches, Collaborative Filtering (CF) approaches, particularly…
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A Multi-Objective Optimization Framework for Data Cleaning Using Large Language Models
The use of Large Language Models (LLMs) in data cleaning tasks has demonstrated impressive capabilities. However, the high inference costs associated with LLMs pose significant challenges, particularly when managing large-scale datasets within constrained budgets. While many studies focus on direct…
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Artikel Jurnal
FD-GNN: Feature Decomposition Graph Neural Network for Anomaly Detection
The objective of multidimensional graph fraud detection is to identify fraudulent entities within a graph. Graph Neural Network (GNN) models leverage graph structures to propagate messages from neighbors to target nodes, thereby obtaining precise representations of the target nodes. However…
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Artikel Jurnal
Image Copyright Dual-Protection Based on Extractable and Imperceptible Adversarial Watermark
Generally, there are two popular ways to protect image copyright, i.e., proactive protection (preventing illegal use via adversarial perturbation) and passive protection (verifying ownership by digital watermarking). However, since the perturbation and watermark embedded into an image will…
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Artikel Jurnal
DRCU-Net: A 3D Segmentation Model for Rectal Tumors Based on Deeply Supervised Residual Capsule Networks
Existing Two-Dimensional (2D) rectal tumor segmentation methods struggle to fully exploit the relationships between slices due to the absence of Three-Dimensional (3D) spatial information, while traditional 3D segmentation techniques often suffer from poor performance and low rotational robustness…
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DPKC: A Privacy-Preserving Availability-Enhanced Clustering Scheme for Data Analysis in IoMT
The advancement of the Internet of Medical Things (IoMT) has rendered the clustering method pivotal in medical data analysis. Nevertheless, the exposure of patient privacy during this process constitutes a significant security concern. To achieve privacy protection for cluster analysis while…
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Artikel Jurnal
TDP-FKGC: Task-Guided Diffusion Prototype Network for Few Shot Knowledge Graph Completion
Recently, Few-shot Knowledge Graph Completion (FKGC) has emerged as a significant research area, yet it encounters challenges stemming from the complexity of multi-semantic relationships in few-shot scenarios. To address these challenges, we propose Task-guided Diffusion Prototype network for FKGC…
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Artikel Jurnal
Frequent Pattern Mining for IoT Big Streaming Data Based on Short-Pattern Graph
Internet of things (IoT) technology is important in the era of big data, and in most IoT scenarios, data are constantly arriving in the form of streams. Streaming data have a fast frequency and a large volume, which, over time, has no upper limit. Streaming data contain much valuable information…
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Artikel Jurnal
Domain-Specific Self-Supervised Contrastive Learning with Contrast-Aware Pair Refinement for Pathological Image Analysis
Deep learning offers notable promise for computational pathology, but its performance is constrained by the need for extensively annotated datasets, which are costly and laborious to produce. Self-Supervised Learning (SSL) provides an effective paradigm for learning discriminative representations…
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Reliable and Secure Anomaly Detection in Heterogeneous Federated Learning: A Comprehensive Review
Anomaly detection plays a critical role in ensuring the security of data and systems across diverse real-world applications. Traditional anomaly detection relies on collecting large datasets on a central server, but in reality, data are often spread across different clients and cannot be directly…
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Artikel Jurnal
COAPT: Bridging Semantic-Operational Divide in Autonomous Penetration Testing Through LLM-Driven Cognitive Planning
The automation of penetration testing has long been constrained by the semantic-operational divide between human expert cognition and machine-executable workflows. We present COAPT, a novel architecture that bridges this gap through large language model (LLM) driven cognitive planning, enabling…
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FilterLDPSyn: Locally Differentially Private Data Synthesis Based on Measurements Filtering
Data synthesis under Local Differential Privacy (LDP) presents a promising approach for private data analysis and sharing, as it enables the execution of all analysis tasks on raw data without the need for a trusted aggregator. The select-measure-generate paradigm of data synthesis under…
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An Intelligent and Latency Efficient Method for IoT-MEC Task Offloading
Mobile Edge Computing (MEC) has emerged as a viable means to improve processing efficiency by reducing distance between computation and Internet of Things (IoT) devices, results in lower latency and energy expenditure. Although MEC appears to be a good candidate for improving task distribution…
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Improving Cross-Modal Semantic Alignment with Cross-Modal Joint Semantic Transformer for Multimodal Sentiment Analysis
Multimodal Sentiment Analysis (MSA) aims to comprehensively understand human affective states. To achieve this goal, it integrates heterogeneous modalities, including text, audio, and visual information. However, semantic misalignment within multimodal data and the insufficiency of multimodal…
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Artikel Jurnal
Detection of Base Modifications Using Long-Read Sequencing: Methods, Applications, and Challenges
Base modifications are fundamental epigenetic marks widely present in both deoxyribonucleic acid (DNA) and ribonucleic acid (RNA), playing crucial roles in regulating gene expression, development, aging, and the pathogenesis of various diseases. Conventional detection methods often depend on harsh…
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Artikel Jurnal
CFL-LSTM: Collaborative Cloud Server Load Prediction Using Multi-Dimensional Time Series Correlation Analysis and LSTM
Accurate forecasting of large-scale cloud server workloads is a critical challenge in modern microservice-based data centers, where complex inter-node dependencies, temporal latency effects, and multi-dimensional fluctuation patterns often undermine the effectiveness of traditional prediction…
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TabMAGD: Combining Masked Autoencoders with Guided Diffusion for Mixed-Type Tabular Data Synthesis
To address the scarcity of real data and data privacy concerns, significant research efforts have been directed toward developing tabular data synthesizers. Tabular data exhibit intrinsic heterogeneity with inter-column correlations, where features may represent diverse information types and…
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Artikel Jurnal
Hypergraph-Enhanced Multimodal Dynamics for Multi-Omics Classification via Intra- and Inter-Sample Fusion
Multimodal learning is increasingly pivotal in biomedical research, where multi-omics technologies enable comprehensive characterization of diverse molecular layers. Despite their potential, effective integration of heterogeneous multi-omics data remains challenging due to high dimensionality…