Natural language processing for humanitarian action: Opportunities, challenges, and the path toward humanitarian NLP [0.03%]
人道主义行动的自然语言处理：机遇、挑战及通向人道主义NLP之路
Roberta Rocca,Nicolò Tamagnone,Selim Fekih et al.
Roberta Rocca et al.
Natural language processing (NLP) is a rapidly evolving field at the intersection of linguistics, computer science, and artificial intelligence, which is concerned with developing methods to process and generate language at scale. Modern NL...
Dietmar Jannach,Himan Abdollahpouri
Dietmar Jannach
Recommender systems can be characterized as software solutions that provide users with convenient access to relevant content. Traditionally, recommender systems research predominantly focuses on developing machine learning algorithms that a...
Personalized diversification of complementary recommendations with user preference in online grocery [0.03%]
基于用户偏好的在线杂货推荐的互补多样性个性化研究
Luyi Ma,Nimesh Sinha,Jason H D Cho et al.
Luyi Ma et al.
Complementary recommendations play an important role in surfacing the relevant items to the customers. In the cross-selling scenario, some customers might present more exploratory shopping behaviors and prefer more diverse complements, whil...
A large-scale machine learning study of sociodemographic factors contributing to COVID-19 severity [0.03%]
一项关于社会人口因素导致新冠肺炎病情加重的大规模机器学习研究
Marko Tumbas,Sofija Markovic,Igor Salom et al.
Marko Tumbas et al.
Understanding sociodemographic factors behind COVID-19 severity relates to significant methodological difficulties, such as differences in testing policies and epidemics phase, as well as a large number of predictors that can potentially co...
CURTAINs for your sliding window: Constructing unobserved regions by transforming adjacent intervals [0.03%]
窗帘：通过转换邻域区间进行不可观测区域的构建
John Andrew Raine,Samuel Klein,Debajyoti Sengupta et al.
John Andrew Raine et al.
We propose a new model independent technique for constructing background data templates for use in searches for new physics processes at the LHC. This method, called Curtains, uses invertible neural networks to parameterise the distribution...
Examining the relationship between big data analytics capabilities and organizational ambidexterity in the Malaysian banking sector [0.03%]
马来西亚银行业大数据分析能力与组织双刃剑关系的研究
Norzalita Abd Aziz,Fei Long
Norzalita Abd Aziz
Drawing on previous literature on dynamic capability view (DCV), we examine the effects of data analytics capabilities (BDAC) on organizational ambidexterity and the paradoxical tensions between exploration and exploitation in the Malaysian...
CRMnet: A deep learning model for predicting gene expression from large regulatory sequence datasets [0.03%]
基于大规模调控序列数据集的基因表达预测的深度学习模型CRMnet
Ke Ding,Gunjan Dixit,Brian J Parker et al.
Ke Ding et al.
Recent large datasets measuring the gene expression of millions of possible gene promoter sequences provide a resource to design and train optimized deep neural network architectures to predict expression from sequences. High predictive per...
Corrigendum: SemNet: Learning semantic attributes for human activity recognition with deep belief networks [0.03%]
纠错:SemNet:运用深度信念网络学习语义属性进行人类活动识别
Shanmuga Venkatachalam,Harideep Nair,Ming Zeng et al.
Shanmuga Venkatachalam et al.
[This corrects the article DOI: 10.3389/fdata.2022.879389.]. Keywords: artificial intelligence; deep belief ...
Published Erratum
Frontiers in big data. 2023 Mar 10:6:1170820. DOI:10.3389/fdata.2023.1170820 2023
Nhu Y Tran,Huynh Trung Hieu,Pham The Bao
Nhu Y Tran
In image segmentation, there are many methods to accomplish the result of segmenting an image into k clusters. However, the number of clusters k is always defined before running the process. It is defined by some observation or knowledge ba...
Mohammad Minhazul Haq,Hehuan Ma,Junzhou Huang
Mohammad Minhazul Haq
The accurate segmentation of nuclei is crucial for cancer diagnosis and further clinical treatments. To successfully train a nuclei segmentation network in a fully-supervised manner for a particular type of organ or cancer, we need the data...