Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance [0.03%]
基于相关性的 syndrome surveillance 中疾病模式的挖掘算法研究
Michael Rapp,Moritz Kulessa,Eneldo Loza Mencía et al.
Michael Rapp et al.
Early outbreak detection is a key aspect in the containment of infectious diseases, as it enables the identification and isolation of infected individuals before the disease can spread to a larger population. Instead of detecting unexpected...
Top-Down Machine Learning-Based Architecture for Cyberattacks Identification and Classification in IoT Communication Networks [0.03%]
基于自上而下机器学习的物联网通信网络 cyberattack 识别与分类架构
Qasem Abu Al-Haija
Qasem Abu Al-Haija
With the prompt revolution and emergence of smart, self-reliant, and low-power devices, Internet of Things (IoT) has inconceivably expanded and impacted almost every real-life application. Nowadays, for example, machines and devices are now...
Yijun Tian,Chuxu Zhang,Ronald Metoyer et al.
Yijun Tian et al.
Recipe recommendation systems play an important role in helping people find recipes that are of their interest and fit their eating habits. Unlike what has been developed for recommending recipes using content-based or collaborative filteri...
Corrigendum: The Rise of Populism and the Reconfiguration of the German Political Space [0.03%]
德国政坛民粹主义崛起及政局重组корректор: 民粹主义的兴起和德国政治空间的重构
Eckehard Olbrich,Sven Banisch
Eckehard Olbrich
[This corrects the article DOI: 10.3389/fdata.2021.731349.]. Keywords: network analysis; party competition; ...
Published Erratum
Frontiers in big data. 2022 Jan 11:4:833037. DOI:10.3389/fdata.2021.833037 2022
The Effects of Gender Signals and Performance in Online Product Reviews [0.03%]
网络产品评论中的性别信号及绩效表现效应研究
Sandipan Sikdar,Rachneet Sachdeva,Johannes Wachs et al.
Sandipan Sikdar et al.
This work quantifies the effects of signaling gender through gender specific user names, on the success of reviews written on the popular amazon.com shopping platform. Highly rated reviews play an important role in e-commerce since they are...
Preparing Distributed Computing Operations for the HL-LHC Era With Operational Intelligence [0.03%]
利用运营智能为HL-LHC时代准备分布式计算操作
Alessandro Di Girolamo,Federica Legger,Panos Paparrigopoulos et al.
Alessandro Di Girolamo et al.
As a joint effort from various communities involved in the Worldwide LHC Computing Grid, the Operational Intelligence project aims at increasing the level of automation in computing operations and reducing human interventions. The distribut...
The Bayes Estimators of the Variance and Scale Parameters of the Normal Model With a Known Mean for the Conjugate and Noninformative Priors Under Stein's Loss [0.03%]
Stein损失下共轭先验和非信息先验的方差和尺度参数的Bayes估计
Ying-Ying Zhang,Teng-Zhong Rong,Man-Man Li
Ying-Ying Zhang
For the normal model with a known mean, the Bayes estimation of the variance parameter under the conjugate prior is studied in Lehmann and Casella (1998) and Mao and Tang (2012). However, they only calculate the Bayes estimator with respect...
Are You Willing to Self-Disclose for Science? Effects of Privacy Awareness and Trust in Privacy on Self-Disclosure of Personal and Health Data in Online Scientific Studies-An Experimental Study [0.03%]
您愿意为了科学而自我披露吗？隐私意识和对隐私信任对于在线科学研究中个人及健康数据的自我披露的影响-一项实验研究
Cornelia Herbert,Verena Marschin,Benjamin Erb et al.
Cornelia Herbert et al.
Digital interactions via the internet have become the norm rather than the exception in our global society. Concerns have been raised about human-centered privacy and the often unreflected self-disclosure behavior of internet users. This st...
Computational Modeling of Hierarchically Polarized Groups by Structured Matrix Factorization [0.03%]
基于结构化矩阵分解的层级群体偏向性计算模型研究
Dachun Sun,Chaoqi Yang,Jinyang Li et al.
Dachun Sun et al.
The paper extends earlier work on modeling hierarchically polarized groups on social media. An algorithm is described that 1) detects points of agreement and disagreement between groups, and 2) divides them hierarchically to represent neste...
Weighting Methods for Rare Event Identification From Imbalanced Datasets [0.03%]
不平衡数据集中罕见事件识别的加权方法研究
Jia He,Maggie X Cheng
Jia He
In machine learning, we often face the situation where the event we are interested in has very few data points buried in a massive amount of data. This is typical in network monitoring, where data are streamed from sensing or measuring unit...