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The differences in gastric cancer epidemiological data between SEER and GBD: a joinpoint and age-period-cohort analysis J. Big Data (IF 8.1) Pub Date : 2024-04-13 Zenghong Wu, Kun Zhang, Weijun Wang, Mengke Fan, Rong Lin
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Enhancing academic performance prediction with temporal graph networks for massive open online courses J. Big Data (IF 8.1) Pub Date : 2024-04-13 Qionghao Huang, Jili Chen
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DAPS diagrams for defining Data Science projects J. Big Data (IF 8.1) Pub Date : 2024-04-12 Jeroen de Mast, Joran Lokkerbol
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B-CAT: a model for detecting botnet attacks using deep attack behavior analysis on network traffic flows J. Big Data (IF 8.1) Pub Date : 2024-04-10 Muhammad Aidiel Rachman Putra, Tohari Ahmad, Dandy Pramana Hostiadi
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Computer aided technology based on graph sample and aggregate attention network optimized for soccer teaching and training J. Big Data (IF 8.1) Pub Date : 2024-04-05 Guanghui Yang, Xinyuan Feng
Football is the most popular game in the world and has significant influence on various aspects including politics, economy and culture. The experience of the football developed nation has shown that the steady growth of youth football is crucial for elevating a nation's overall football proficiency. It is essential to develop techniques and create strategies that adapt to their individual physical
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Adapting transformer-based language models for heart disease detection and risk factors extraction J. Big Data (IF 8.1) Pub Date : 2024-04-04 Essam H. Houssein, Rehab E. Mohamed, Gang Hu, Abdelmgeid A. Ali
Efficiently treating cardiac patients before the onset of a heart attack relies on the precise prediction of heart disease. Identifying and detecting the risk factors for heart disease such as diabetes mellitus, Coronary Artery Disease (CAD), hyperlipidemia, hypertension, smoking, familial CAD history, obesity, and medications is critical for developing effective preventative and management measures
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Gene selection via improved nuclear reaction optimization algorithm for cancer classification in high-dimensional data J. Big Data (IF 8.1) Pub Date : 2024-04-03
Abstract RNA Sequencing (RNA-Seq) has been considered a revolutionary technique in gene profiling and quantification. It offers a comprehensive view of the transcriptome, making it a more expansive technique in comparison with micro-array. Genes that discriminate malignancy and normal can be deduced using quantitative gene expression. However, this data is a high-dimensional dense matrix; each sample
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The role of classifiers and data complexity in learned Bloom filters: insights and recommendations J. Big Data (IF 8.1) Pub Date : 2024-03-27 Dario Malchiodi, Davide Raimondi, Giacomo Fumagalli, Raffaele Giancarlo, Marco Frasca
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Feature selection strategies: a comparative analysis of SHAP-value and importance-based methods J. Big Data (IF 8.1) Pub Date : 2024-03-26 Huanjing Wang, Qianxin Liang, John T. Hancock, Taghi M. Khoshgoftaar
In the context of high-dimensional credit card fraud data, researchers and practitioners commonly utilize feature selection techniques to enhance the performance of fraud detection models. This study presents a comparison in model performance using the most important features selected by SHAP (SHapley Additive exPlanations) values and the model’s built-in feature importance list. Both methods rank
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Multi-sample $$\zeta $$ -mixup: richer, more realistic synthetic samples from a p-series interpolant J. Big Data (IF 8.1) Pub Date : 2024-03-23
Abstract Modern deep learning training procedures rely on model regularization techniques such as data augmentation methods, which generate training samples that increase the diversity of data and richness of label information. A popular recent method, mixup, uses convex combinations of pairs of original samples to generate new samples. However, as we show in our experiments, mixup can produce undesirable
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Learning manifolds from non-stationary streams J. Big Data (IF 8.1) Pub Date : 2024-03-23 Suchismit Mahapatra, Varun Chandola
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An adaptive hybrid african vultures-aquila optimizer with Xgb-Tree algorithm for fake news detection J. Big Data (IF 8.1) Pub Date : 2024-03-19 Amr A. Abd El-Mageed, Amr A. Abohany, Asmaa H. Ali, Khalid M. Hosny
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Integration of transcriptomic analysis and multiple machine learning approaches identifies NAFLD progression-specific hub genes to reveal distinct genomic patterns and actionable targets J. Big Data (IF 8.1) Pub Date : 2024-03-15 Jing Sun, Run Shi, Yang Wu, Yan Lou, Lijuan Nie, Chun Zhang, Yutian Cao, Qianhua Yan, Lifang Ye, Shu Zhang, Xuanbin Wang, Qibiao Wu, Xuehua Jiao, Jiangyi Yu, Zhuyuan Fang, Xiqiao Zhou
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Where you go is who you are: a study on machine learning based semantic privacy attacks J. Big Data (IF 8.1) Pub Date : 2024-03-12 Nina Wiedemann, Krzysztof Janowicz, Martin Raubal, Ourania Kounadi
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Synthesizing class labels for highly imbalanced credit card fraud detection data J. Big Data (IF 8.1) Pub Date : 2024-03-09 Robert K. L. Kennedy, Flavio Villanustre, Taghi M. Khoshgoftaar, Zahra Salekshahrezaee
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The adaptive community-response (ACR) method for collecting misinformation on social media J. Big Data (IF 8.1) Pub Date : 2024-02-24 Julian Kauk, Helene Kreysa, André Scherag, Stefan R. Schweinberger
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Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning J. Big Data (IF 8.1) Pub Date : 2024-02-24 Jing Li, Mohd Shahizan Othman, Hewan Chen, Lizawati Mi Yusuf
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Measuring regularity of human physical activities with entropy models J. Big Data (IF 8.1) Pub Date : 2024-02-24 Keqin Shi, Zhen Chen, Weiqiang Sun, Weisheng Hu
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Data-driven multinomial random forest: a new random forest variant with strong consistency J. Big Data (IF 8.1) Pub Date : 2024-02-23 JunHao Chen, XueLi Wang, Fei Lei
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Comprehensive study of driver behavior monitoring systems using computer vision and machine learning techniques J. Big Data (IF 8.1) Pub Date : 2024-02-22 Fangming Qu, Nolan Dang, Borko Furht, Mehrdad Nojoumian
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Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction J. Big Data (IF 8.1) Pub Date : 2024-02-22 Md. Alamin Talukder, Md. Manowarul Islam, Md Ashraf Uddin, Khondokar Fida Hasan, Selina Sharmin, Salem A. Alyami, Mohammad Ali Moni
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Algorithms of the Möbius function by random forests and neural networks J. Big Data (IF 8.1) Pub Date : 2024-02-21 Huan Qin, Yangbo Ye
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Can we predict multi-party elections with Google Trends data? Evidence across elections, data windows, and model classes J. Big Data (IF 8.1) Pub Date : 2024-02-17 Jan Behnert, Dean Lajic, Paul C. Bauer
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Deep learning enables the quantification of browning capacity of human adipose samples J. Big Data (IF 8.1) Pub Date : 2024-02-11 Yuxin Wang, Shiman Zuo, Nanfei Yang, Ani Jian, Wei Zheng, Zichun Hua, Pingping Shen
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Federated Freeze BERT for text classification J. Big Data (IF 8.1) Pub Date : 2024-02-09 Omar Galal, Ahmed H. Abdel-Gawad, Mona Farouk
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Internal dynamics of patent reference networks using the Bray–Curtis dissimilarity measure J. Big Data (IF 8.1) Pub Date : 2024-02-04 József Baranyi, Szilveszter Csorba, Zsuzsa Farkas, Tünde Pacza, Ákos Józwiak
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Conventional dendritic cell 2 links the genetic causal association from allergic asthma to COVID-19: a Mendelian randomization and transcriptomic study J. Big Data (IF 8.1) Pub Date : 2024-02-04 Hua Liu, Siting Huang, Liting Yang, Hongshu Zhou, Bo Chen, Lisha Wu, Liyang Zhang
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Survey of transformers and towards ensemble learning using transformers for natural language processing J. Big Data (IF 8.1) Pub Date : 2024-02-04
Abstract The transformer model is a famous natural language processing model proposed by Google in 2017. Now, with the extensive development of deep learning, many natural language processing tasks can be solved by deep learning methods. After the BERT model was proposed, many pre-trained models such as the XLNet model, the RoBERTa model, and the ALBERT model were also proposed in the research community
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A novel approach for detecting deep fake videos using graph neural network J. Big Data (IF 8.1) Pub Date : 2024-02-01
Abstract Deep fake technology has emerged as a double-edged sword in the digital world. While it holds potential for legitimate uses, it can also be exploited to manipulate video content, causing severe social and security concerns. The research gap lies in the fact that traditional deep fake detection methods, such as visual quality analysis or inconsistency detection, need help to keep up with the
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A machine learning-based credit risk prediction engine system using a stacked classifier and a filter-based feature selection method J. Big Data (IF 8.1) Pub Date : 2024-02-01 Ileberi Emmanuel, Yanxia Sun, Zenghui Wang
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Hybrid wrapper feature selection method based on genetic algorithm and extreme learning machine for intrusion detection J. Big Data (IF 8.1) Pub Date : 2024-02-01
Abstract Intrusion detection systems play a critical role in the mitigation of cyber-attacks on the Internet of Things (IoT) environment. Due to the integration of many devices within the IoT environment, a huge amount of data is generated. The generated data sets in most cases consist of irrelevant and redundant features that affect the performance of the existing intrusion detection systems (IDS)
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Dual channel and multi-scale adaptive morphological methods for infrared small targets J. Big Data (IF 8.1) Pub Date : 2024-02-01 Ying-Bin Liu, Yu-Hui Zeng, Jian-Hua Qin
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Generalized Estimating Equations Boosting (GEEB) machine for correlated data J. Big Data (IF 8.1) Pub Date : 2024-01-22
Abstract Rapid development in data science enables machine learning and artificial intelligence to be the most popular research tools across various disciplines. While numerous articles have shown decent predictive ability, little research has examined the impact of complex correlated data. We aim to develop a more accurate model under repeated measures or hierarchical data structures. Therefore, this
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A review of graph neural networks: concepts, architectures, techniques, challenges, datasets, applications, and future directions J. Big Data (IF 8.1) Pub Date : 2024-01-16 Bharti Khemani, Shruti Patil, Ketan Kotecha, Sudeep Tanwar
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Block size estimation for data partitioning in HPC applications using machine learning techniques J. Big Data (IF 8.1) Pub Date : 2024-01-16 Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino, Domenico Talia, Paolo Trunfio, Rosa M. Badia, Jorge Ejarque, Fernando Vázquez-Novoa
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Bilingual video captioning model for enhanced video retrieval J. Big Data (IF 8.1) Pub Date : 2024-01-16
Abstract Many video platforms rely on the descriptions that uploaders provide for video retrieval. However, this reliance may cause inaccuracies. Although deep learning-based video captioning can resolve this problem, it has some limitations: (1) traditional keyframe extraction techniques do not consider video length/content, resulting in low accuracy, high storage requirements, and long processing
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Cyberattack detection in wireless sensor networks using a hybrid feature reduction technique with AI and machine learning methods J. Big Data (IF 8.1) Pub Date : 2024-01-13
Abstract This paper proposes an intelligent hybrid model that leverages machine learning and artificial intelligence to enhance the security of Wireless Sensor Networks (WSNs) by identifying and preventing cyberattacks. The study employs feature reduction techniques, including Singular Value Decomposition (SVD) and Principal Component Analysis (PCA), along with the K-means clustering model enhanced
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Gct-TTE: graph convolutional transformer for travel time estimation J. Big Data (IF 8.1) Pub Date : 2024-01-13 Vladimir Mashurov, Vaagn Chopuryan, Vadim Porvatov, Arseny Ivanov, Natalia Semenova
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The state of metaverse research: a bibliometric visual analysis based on CiteSpace J. Big Data (IF 8.1) Pub Date : 2024-01-10 Huike Li, Bo Li
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CNN-IKOA: convolutional neural network with improved Kepler optimization algorithm for image segmentation: experimental validation and numerical exploration J. Big Data (IF 8.1) Pub Date : 2024-01-10 Mohamed Abdel-Basset, Reda Mohamed, Ibrahim Alrashdi, Karam M. Sallam, Ibrahim A. Hameed
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RPf-GCNs: reciprocal perspective driven fused GCNs for rumor detection on social media J. Big Data (IF 8.1) Pub Date : 2024-01-09
Abstract The earliest detection of rumors across social media is the need to the hour in present global village. User’s are seamlessly connected in an unstructured network leading to rapid flow of information. User’s on the social media with malign intents may share defamatory content to contribute towards the fifth generation media warfare. The ingress of such defamatory content into society can result
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Prediction of flight departure delays caused by weather conditions adopting data-driven approaches J. Big Data (IF 8.1) Pub Date : 2024-01-09 Seongeun Kim, Eunil Park
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Analysis of customer reviews with an improved VADER lexicon classifier J. Big Data (IF 8.1) Pub Date : 2024-01-07 Kousik Barik, Sanjay Misra
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Blockchain meets machine learning: a survey J. Big Data (IF 8.1) Pub Date : 2024-01-06 Safak Kayikci, Taghi M. Khoshgoftaar
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Data reduction techniques for highly imbalanced medicare Big Data J. Big Data (IF 8.1) Pub Date : 2024-01-03 John T. Hancock, Huanjing Wang, Taghi M. Khoshgoftaar, Qianxin Liang
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Impact of random oversampling and random undersampling on the performance of prediction models developed using observational health data J. Big Data (IF 8.1) Pub Date : 2024-01-03 Cynthia Yang, Egill A. Fridgeirsson, Jan A. Kors, Jenna M. Reps, Peter R. Rijnbeek
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Plant disease detection and classification techniques: a comparative study of the performances J. Big Data (IF 8.1) Pub Date : 2024-01-02 Wubetu Barud Demilie
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Out-of-distribution- and location-aware PointNets for real-time 3D road user detection without a GPU J. Big Data (IF 8.1) Pub Date : 2024-01-02
Abstract 3D road user detection is an essential task for autonomous vehicles and mobile robots, and it plays a key role, for instance, in obstacle avoidance and route planning tasks. Existing solutions for detection require expensive GPU units to run in real-time. This paper presents a light algorithm that runs in real-time without a GPU. The algorithm combines a classical point cloud proposal generator
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Analysis of imprecise measurement data utilizing z-test for correlation J. Big Data (IF 8.1) Pub Date : 2024-01-02 Muhammad Aslam
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Hybrid beluga whale optimization algorithm with multi-strategy for functions and engineering optimization problems J. Big Data (IF 8.1) Pub Date : 2024-01-02 Jiaxu Huang, Haiqing Hu
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Instance segmentation on distributed deep learning big data cluster J. Big Data (IF 8.1) Pub Date : 2024-01-02 Mohammed Elhmadany, Islam Elmadah, Hossam E. Abdelmunim
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Low-shot learning and class imbalance: a survey J. Big Data (IF 8.1) Pub Date : 2024-01-02
Abstract The tasks of few-shot, one-shot, and zero-shot learning—or collectively “low-shot learning” (LSL)—at first glance are quite similar to the long-standing task of class imbalanced learning; specifically, they aim to learn classes for which there is little labeled data available. Motivated by this similarity, we conduct a survey to review the recent literature for works which combine these fields
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A novel intelligent approach for flight delay prediction J. Big Data (IF 8.1) Pub Date : 2023-12-21 Maged Mamdouh, Mostafa Ezzat, Hesham A.Hefny
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A service-categorized security scheme with physical unclonable functions for internet of vehicles J. Big Data (IF 8.1) Pub Date : 2023-12-21 Nadhir Ben Halima, Ala Saleh Alluhaidan, Mohammad Zunnun Khan, Mohd Shahid Husain, Mohammad Ayoub Khan
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Uncertainty-driven generation of neutrosophic random variates from the Weibull distribution J. Big Data (IF 8.1) Pub Date : 2023-12-20
Abstract Objective This paper aims to introduce an algorithm designed for generating random variates in situations characterized by uncertainty. Method The paper outlines the development of two distinct algorithms for producing both minimum and maximum neutrosophic data based on the Weibull distribution. Results Through comprehensive simulations, the efficacy of these algorithms has been thoroughly
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Aspect-level sentiment classification with fused local and global context J. Big Data (IF 8.1) Pub Date : 2023-12-19 Ao Feng, Jiazhi Cai, Zhengjie Gao, Xiaojie Li
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Algorithm for generating neutrosophic data using accept-reject method J. Big Data (IF 8.1) Pub Date : 2023-12-07 Muhammad Aslam, Faten S. Alamri
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The use of class imbalanced learning methods on ULSAM data to predict the case–control status in genome-wide association studies J. Big Data (IF 8.1) Pub Date : 2023-11-30 R. Onur Öztornaci, Hamzah Syed, Andrew P. Morris, Bahar Taşdelen
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Introducing the enterprise data marketplace: a platform for democratizing company data J. Big Data (IF 8.1) Pub Date : 2023-11-24 Rebecca Eichler, Christoph Gröger, Eva Hoos, Christoph Stach, Holger Schwarz, Bernhard Mitschang
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On hierarchical clustering-based approach for RDDBS design J. Big Data (IF 8.1) Pub Date : 2023-11-18 Hassan I. Abdalla, Ali A. Amer, Sri Devi Ravana