Experimental study and clustering of operating staff of search systems in the sense of stress resistance [0.03%]
搜索引擎操作人员的压力承受能力的实证研究与分类
Nataliya Shakhovska,Roman Kaminskyi,Bohdan Khudoba
Nataliya Shakhovska
Introduction: The main goal of this study is to develop a methodology for the organization of experimental selection of operator personnel based on the analysis of their behavior under the influence of micro-stresses. ...
Turker Berk Donmez,Mohammed Mansour,Mustafa Kutlu et al.
Turker Berk Donmez et al.
This paper aims to detect anemia using images of the lip mucosa, where the skin tissue is thin, and to confirm the feasibility of detecting anemia noninvasively and in the home environment using machine learning (ML). Data were collected fr...
How big is Big Data? A comprehensive survey of data production, storage, and streaming in science and industry [0.03%]
大数据有多大？科学与工业中数据制作、存储和流处理的全面调查
Luca Clissa,Mario Lassnig,Lorenzo Rinaldi
Luca Clissa
The contemporary surge in data production is fueled by diverse factors, with contributions from numerous stakeholders across various sectors. Comparing the volumes at play among different big data entities is challenging due to the scarcity...
Namita Gupta
Namita Gupta
Lin-Ching Chang,Anastasia Angelopoulou
Lin-Ching Chang
Corrigendum: Applications and techniques for fast machine learning in science [0.03%]
快科学机器学习的应用和技巧更正版
Allison McCarn Deiana,Nhan Tran,Joshua Agar et al.
Allison McCarn Deiana et al.
[This corrects the article DOI: 10.3389/fdata.2022.787421.]. Keywords: big data; codesign; coprocessors; fas...
Published Erratum
Frontiers in big data. 2023 Oct 16:6:1301942. DOI:10.3389/fdata.2023.1301942 2023
Differential privacy in collaborative filtering recommender systems: a review [0.03%]
基于差分隐私的协同过滤推荐系统研究综述
Peter Müllner,Elisabeth Lex,Markus Schedl et al.
Peter Müllner et al.
State-of-the-art recommender systems produce high-quality recommendations to support users in finding relevant content. However, through the utilization of users' data for generating recommendations, recommender systems threaten users' priv...
Iustina Ivanova,Mike Wald
Iustina Ivanova
Outdoor sport climbing is popular in Northern Italy due to its vast amount of rock climbing places (such as crags). New climbing crags appear yearly, creating an information overload problem for tourists who plan their sport climbing vacati...
Fairness of recommender systems in the recruitment domain: an analysis from technical and legal perspectives [0.03%]
招聘领域中推荐系统的公平性：从技术和法律视角的分析
Deepak Kumar,Tessa Grosz,Navid Rekabsaz et al.
Deepak Kumar et al.
Recommender systems (RSs) have become an integral part of the hiring process, be it via job advertisement ranking systems (job recommenders) for the potential employee or candidate ranking systems (candidate recommenders) for the employer. ...
Rawan Elragal,Ahmed Elragal,Abdolrasoul Habibipour
Rawan Elragal
This research addresses the demanding need for research in healthcare analytics, by explaining how previous studies have used big data, AI, and machine learning to identify, address, or solve healthcare problems. Healthcare science methods ...