检索结果-内蒙古大学图书馆

5th International Conference on Advancements in computing, ICAC 2023

作者： Hemachandra, K.M Tharindu Anupa Sumathipala, Prasanna Athurugiriya, A.A.A Gaweshini Sri Lanka Institute of Information Technology Department of Data Science Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798350358131

Within the hospitality sector, ensuring customer satisfaction takes precedence, particularly in economies such as Sri Lanka, where tourism serves as a vital growth catalyst. Interestingly, disparities often arise between customer ratings and their written evaluations. This study presents an innovative strategy that utilizes semantic search techniques to extract comprehensive insights from customer feedback, leading to the development of a robust hotel scoring system. By exploring intricate emotions via advanced linguistic analysis, this method reveals underlying cues that conventional metrics often overlook. The method's effectiveness is validated through a comparative study with established hotel ratings. This advancement not only refines precise customer satisfaction assessment for hotels but also bears strategic significance for countries aiming to fortify their tourism sectors. In this era centered around data, this research provides a pivotal standpoint for optimizing hospitality evaluation, thereby enriching guest experiences, and guiding well-informed operational choices. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Determining environmental indicators related to the propagation of contagious diseases and health issues: A Systematic Literature Review 18

Determining environmental indicators related to the propagat...

引用

18th Iberian Conference on Information Systems and Technologies, CISTI 2023

作者： Portillo, Janeth Dominguez Peralta, Laura M. Rodriguez Sampaio, Paulo N. M. Nunes, Eldman De Oliveira Faculty of Information Technologies and Data Science Mexico Graduate Program in Computing and Systems Bahia Salvador Brazil

ISBN: (纸本)9789893347928

The environmental indicators provide significant information in order to describe the state of a phenomenon, environment or area [1]. This paper addresses the indicators present in the air and their relationship in the accommodation and transmission of viruses, as well as how these environmental indicators can lead to health problems. Therefore, the main goal of this work is to review the scientific contributions in the literature in order to determine and select the potential environmental indicators present in indoor environments which have an impact on the health of people who work and live within these spaces. For this purpose, we carried out a Systematic Literature Review (SLR) related to environmental monitoring, COVID-19, Internet of things, air pollution and environmental indicators within indoor spaces. This SLR allowed us to identify indicators that according to their level of presence can represent a high risk for people's health. Therefore, the process of planning, conducting and reporting the Systematic Literature Review enabled us not only to identify some environmental indicators, but also their corresponding monitoring advantages and disadvantages, and multiple perspectives and approaches of each contribution in the literature. Further on, this study will be the basis for the proposal of an automatic and intelligent platform based on Internet of Things for monitoring indoor environments in order to detect high risk levels for the contamination of contagious diseases. © 2023 ITMA.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Graph Disentangled Collaborative Filtering based on Multi-order Similarity Constraint 10

Graph Disentangled Collaborative Filtering based on Multi-or...

引用

10th IEEE International Conference on data science and Advanced Analytics, DSAA 2023

作者： Liu, Yaoze Du, Junwei Li, Haojie Liu, Guanfeng Qingdao University of Science and Technology School of Data Science Qingdao China Macquarie University School of Computing North Ryde Australia

ISBN: (纸本)9798350345032

Disentangled collaborative filtering can explicitly generate embeddings based on users' interests and help improve the interpretability and robustness of recommendations. However, the existing disentangled graph collaborative filtering methods rely solely on direct interaction constraints between nodes to learn node embeddings, which cannot represent higher-order constraints between nodes and node-type differences, resulting in suboptimal node representations and negatively affecting recommendation performance. To address this problem, we propose a Multi-order Similarity Constraint Disentangled Graph Collaborative Filtering (DGCF-MSC) method, which considers not only direct interaction constraints between nodes but also designs a neighborhood enhancement mechanism based on high-order relationships between homogeneous nodes. We realize the disentanglement of heterogeneous type nodes in different feature spaces in a graph convolutional neural network to make the generated embedding more interpretable and improve the performance of graph collaborative filtering. We conduct extensive experiments with three recommendation system datasets and the results demonstrate that DGCF-MSC outperforms the existing disentangled graph collaborative filtering methods in all performance metrics. Our code is released on https://***/lustrelake/DGCF_MSC. © 2023 IEEE.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

SYSTEM THINKING MEETS data science/ENGINEERING 67

SYSTEM THINKING MEETS DATA SCIENCE/ENGINEERING

引用

67th Annual Meeting of the International Society for the Systems sciences, ISSS 2023

作者： Malele, Vusumuzi Unit for Data Science and Computing School of Computer Science and Information Systems North-West University Vanderbijlpark Campus South Africa

ISBN: (纸本)9781713893455

With the advent of data 3.0 and analytics 3.0, system thinkers are in the position to provide a bigger picture in data science and data engineering. In the data life cycle, a system thinking approach emphasises data-driven decision-making. A System Thinker approaches problem-solving by viewing the problems as part of a wider, data-resourced and dynamic system, and a data Practitioner supports the data life cycle by collecting, transforming, and analyzing data, and communicating results to inform and guide decision-making. This paper uses explanatory research and a pragmatic case study approach to look at the (i) What is the role of system thinking and data science/engineering skill in data-driven decision-making or organisation? (ii) Does the combination of system thinking and data science/engineering give rise to a new discipline? (iii) What are the skills needed in this new discipline? The research shows that the system thinking skills in the data life cycle are important. System thinkers meet data practitioners to provide a bigger picture of data-driven decision-making. The latter ascertains the position of a system thinker in any industrial revolution (i.e. industry 4.0. and industry 5.0). Furthermore, a data-System Thinker is proposed as a new career field. © Copyright, Author (Creative Commons), 2023.

关键词： Systems thinking

来源：评论

学校读者我要写书评

暂无评论

SDGNN: Symmetry-Preserving Dual-Stream Graph Neural Networks

引用

IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1717-1719页

作者： Jiufang Chen Ye Yuan Xin Luo the College of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing 400065 the Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China the College of Computer and Information Science Southwest UniversityChongqing 400715China IEEE

Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) are influential instruments for representation learning to a UWG, they invariably adopt a unique node feature matrix for illustrating the sole node set of a UWG.

关键词： representation preserving undirected

来源：评论

学校读者我要写书评

暂无评论

Developing a Visual Dashboard to Improve Research Activity Assessment 11

Developing a Visual Dashboard to Improve Research Activity A...

引用

11th International Conference on Computer, Control, Informatics and its Applications, IC3INA 2024

作者： Nur Rahman, Muhammad Zaki Prakasa, Esa Bijaksana, Moch Arif Bachelor of Data Science Faculty of Informatics Telkom University Bandung Indonesia Bandung Indonesia School of Computing Telkom University Bandung Indonesia

ISBN: (纸本)9798331542313

In research institutions, the ability to monitor and analyze publication output is crucial for assessing productivity and achieving strategic goals. This paper presents a dashboard designed to visualize and analyze publication data from a research center of the Indonesian public institution. The dashboard addresses several key questions: (1) whether the current number of publications is on track to meet the institution’s targets, (2) the comparison between journal and proceeding publications, (3) individual researcher productivity, (4) research group productivity, and (5) the collaborative efforts among researchers and groups. By leveraging this tool, stakeholders can gain insights into publication trends and identify areas for improvement. The findings reveal significant trends in publication types and collaboration patterns, offering a comprehensive overview of the institution’s research output. This study contributes to the understanding of research productivity metrics and their implications for strategic planning in academic research. © 2024 IEEE.

关键词： Collaboration Metrics Dashboard Visualization Publication data Research Productivity

来源：评论

学校读者我要写书评

暂无评论

A TRUST-REGION METHOD FOR SOLVING TRUNCATED COMPLEX SINGULAR VALUE DECOMPOSITION

引用

Journal of Computational Mathematics 2024年第4期42卷 999-1031页

作者： Jiaofen Li Lingchang Kong Xuefeng Duan Xuelin Zhou Qilun Luo School of Mathematics and Computing Science Guangxi Colleges and Universities Key Laboratory of Data Analysis and ComputationGuangxi Key Laboratory of Automatic Detecting Technology and InstrumentsGuilin University of Electronic TechnologyCenter for Applied Mathematics of Guangxi(GUET)Guilin 541004China School of Mathematical Sciences South China Normal UniversityGuangzhou 510000China School of Mathematics and Computing Science Guilin University of Electronic TechnologyGuilin 541004China School of Mathematics and Computing Science Guangxi Colleges and Universities Key Laboratory of Data Analysis and ComputationGuilin University of Electronic TechnologyCenter for Applied Mathematics of Guangxi(GUET)Guilin 541004China School of Mathematics and Statistics Yunan UniversityKunming 650000China

The truncated singular value decomposition has been widely used in many areas of science including engineering,and statistics,*** this paper,the original truncated complex singular value decomposition problem is formulated as a Riemannian optimiza-tion problem on a product of two complex Stiefel manifolds,a practical algorithm based on the generic Riemannian trust-region method of Absil et *** presented to solve the underlying problem,which enjoys the global convergence and local superlinear conver-gence *** experiments are provided to illustrate the efficiency of the proposed *** with some classical Riemannian gradient-type methods,the existing Riemannian version of limited-memory BFGS algorithms in the MATLAB toolbox Manopt and the Riemannian manifold optimization library ROPTLIB,and some latest infeasible methods for solving manifold optimization problems,are also provided to show the merits of the proposed approach.

关键词： Truncated singular value decomposition Riemannian optimization Trust-region method

来源：评论

学校读者我要写书评

暂无评论

APPLICATION OF GENERATIVE ARTIFICIAL INTELLIGENCE FOR EPIDEMIC MODELING

APPLICATION OF GENERATIVE ARTIFICIAL INTELLIGENCE FOR EPIDEM...

引用

2024 Winter Simulation Conference, WSC 2024

作者： Villaplana, Hannah Danielle Ladera Kwak, Jaeyoung Lees, Michael H. Li, Hongying Cai, Wentong College of Computing and Data Science Nanyang Technological University Singapore Singapore Informatics Institute University of Amsterdam Amsterdam Netherlands Department of Fluid Dynamics Institute of High Performance Computing Singapore Singapore

ISBN: (纸本)9798331534202

Epidemic models have become increasingly useful, especially in the wake of the recent COVID-19 pandemic, emphasizing the crucial role of human behavior in the spread of disease. There has been a recent rise in the usage and popularity of generative artificial intelligence (GenAI), such as ChatGPT especially with its ability to mimic human behavior. In this study, we demonstrate a novel application of GenAI for epidemic modeling. We employed GenAI for creating agents living in a hypothetical town in simulations and simulating their behavior within the context of an ongoing pandemic. We performed a series of simulations to quantify the impact of agent traits and the availability of information for health condition, virus, and government guidelines on the disease spread patterns in terms of peak time and epidemic duration. We also characterized the most influential factors in agents’ decision-making using random forest model. © 2024 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

The implicit bias of adam on separable data 24

The implicit bias of adam on separable data

引用

Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Chenyang Zhang Difan Zou Yuan Cao Department of Statistics and Actuarial Science School of Computing and Data Science The University of Hong Kong Department of Computer Science School of Computing and Data Science & Institute of Data Science The University of Hong Kong Department of Statistics and Actuarial Science School of Computing and Data Science & Department of Mathematics The University of Hong Kong

ISBN: (纸本)9798331314385

Adam has become one of the most favored optimizers in deep learning problems. Despite its success in practice, numerous mysteries persist regarding its theoretical understanding. In this paper, we study the implicit bias of Adam in linear logistic regression. Specifically, we show that when the training data are linearly separable, the iterates of Adam converge towards a linear classifier that achieves the maximum ℓ∞ -margin in direction. Notably, for a general class of diminishing learning rates, this convergence occurs within polynomial time. Our result shed light on the difference between Adam and (stochastic) gradient descent from a theoretical perspective.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Alignment Work for Urban Accessibility: A Study of How Wheelchair Users Travel in Urban Spaces

引用

Proceedings of the ACM on Human-Computer Interaction 2022年第CSCW2期6卷 1–22页

作者： Wu, Yiying Ding, Xianghua Dai, Xuelan Zhang, Peng Lu, Tun Gu, Ning School of Computer Science Shanghai Key Laboratory of Data Science Fudan University Shanghai China School of Computing Science University of Glasgow Glasgow United Kingdom

Mobility is the key for people with disabilities to have full participation in life. To support their mobility, previous work primarily focused on accessibility as an attribute of the external environment to be evaluated, labeled, visualized, and improved. Relatively less work has looked at how people with disabilities go out and move around in practice and work to achieve mobility. This paper presents a qualitative study of 14 wheelchair users' travel practices in everyday life in China, highlighting urban accessibility as alignment work-the use of an awareness of the conditions along the journey to continuously align and re-Align various resources to ensure accessibility and mobility across contexts and moments. By highlighting alignment work, we present another side of the story of urban accessibility, and broaden design considerations to support mobility for wheelchair users. © 2022 ACM.

关键词： Alignment

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：