Efficient community detection in multilayer networks using boolean compositions [0.03%]
基于布尔运算的多层网络社区发现方法
Abhishek Santra,Fariba Afrin Irany,Kamesh Madduri et al.
Abhishek Santra et al.
Networks (or graphs) are used to model the dyadic relations between entities in complex systems. Analyzing the properties of the networks reveal important characteristics of the underlying system. However, in many disciplines, including soc...
Universal skepticism of ChatGPT: a review of early literature on chat generative pre-trained transformer [0.03%]
通用的ChatGPT怀疑论：早期文献综述式聊天生成预训练变换器
Casey Watters,Michal K Lemanski
Casey Watters
ChatGPT, a new language model developed by OpenAI, has garnered significant attention in various fields since its release. This literature review provides an overview of early ChatGPT literature across multiple disciplines, exploring its ap...
Comorbidity network analysis using graphical models for electronic health records [0.03%]
基于图形模型的电子健康记录共病网络分析
Bo Zhao,Sarah Huepenbecker,Gen Zhu et al.
Bo Zhao et al.
Importance: The comorbidity network represents multiple diseases and their relationships in a graph. Understanding comorbidity networks among critical care unit (CCU) patients can help doctors diagnose patients faster, mi...
Discovering anomalies in big data: a review focused on the application of metaheuristics and machine learning techniques [0.03%]
大数据中的异常值挖掘：元启发式和机器学习算法综述
Claudia Cavallaro,Vincenzo Cutello,Mario Pavone et al.
Claudia Cavallaro et al.
With the increase in available data from computer systems and their security threats, interest in anomaly detection has increased as well in recent years. The need to diagnose faults and cyberattacks has also focused scientific research on ...
Synthetic biomedical data generation in support of In Silico Clinical Trials [0.03%]
合成生物医学数据生成支持计算机临床试验
Alena Simalatsar
Alena Simalatsar
Living in the era of Big Data, one may advocate that the additional synthetic generation of data is redundant. However, to be able to truly say whether it is valid or not, one needs to focus more on the meaning and quality of data than on t...
Multi-list interfaces for recommender systems: survey and future directions [0.03%]
推荐系统的多列表接口：调查与未来方向研究
Benedikt Loepp
Benedikt Loepp
For a long time, recommender systems presented their results in the form of simple item lists. In recent years, however, multi-list interfaces have become the de-facto standard in industry, presenting users with numerous collections of reco...
Jonathan Middleton,Jaakko Hakulinen,Katariina Tiitinen et al.
Jonathan Middleton et al.
The process of transforming data into sounds for auditory display provides unique user experiences and new perspectives for analyzing and interpreting data. A research study for data transformation to sounds based on musical elements, calle...
Proliferation of atmospheric datasets can hinder policy making: a data blending technique offers a solution [0.03%]
大气数据集的激增可能阻碍政策制定：一种数据融合技术提供了解决方案
Hamish Steptoe,Theo Economou
Hamish Steptoe
The proliferation of atmospheric datasets is a key outcome from the continued development and advancement of our collective scientific understanding. Yet often datasets describing ostensibly identical processes or atmospheric variables prov...
Artificial intelligence research strategy of the United States: critical assessment and policy recommendations [0.03%]
美国人工职能研究战略：批评与政策建议
Furkan Gursoy,Ioannis A Kakadiaris
Furkan Gursoy
The foundations of Artificial Intelligence (AI), a field whose applications are of great use and concern for society, can be traced back to the early years of the second half of the 20th century. Since then, the field has seen increased res...
Kernel-wise difference minimization for convolutional neural network compression in metaverse [0.03%]
元宇宙中基于卷积神经网络内核差分最小化的模型压缩方法
Yi-Ting Chang
Yi-Ting Chang
Convolutional neural networks have achieved remarkable success in computer vision research. However, to further improve their performance, network models have become increasingly complex and require more memory and computational resources. ...