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检索条件"任意字段=2019 International Conference on Modeling, Simulation and Big Data Analysis（MSBDA 2019）"

共 1293 条记录，以下是11-20 订阅

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How Does Fake News Spread: Raising Awareness & Educating the Public with a simulation Tool

How Does Fake News Spread: Raising Awareness & Educating the...

引用

IEEE international conference on big data (big data)

作者： Lee, Cheng L. Wong, Joel-David J. J. Lim, Zi Y. Tho, Belinda S. T. Kwek, Sean S. W. Shim, Kyong Jin Singapore Management Univ Sch Informat Syst Singapore Singapore

ISBN: (纸本)9781728108582

In this study, we analyze the phenomenon of 'fake news' spreading in the Internet. In recent years, the number of fake news and misinformation spreading cases increased. We analyze vaccine-related fake news spreading in Twitter and discover techniques used by the participants of fake news spreading. We present a simulation game designed to teach the public about the techniques behind fake news spreading.

关键词： fake news sentiment analysis social media analytics

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Fusion modeling and Heterogeneous simulation of big data Technology in 5G Communication Network 4

Fusion Modeling and Heterogeneous Simulation of Big Data Tec...

引用

4th international conference on Smart Systems and Inventive Technology, ICSSIT 2022

作者： Liu, Taiwei Wang, Caifeng Fu, Haiyan Lei, Tengfei Qilu Institute of Technology Shandong Jinan250000 China

ISBN: (纸本)9781665401180

In order to continuously improve the service capabilities of the 5G communication network and promote the formation of a high-quality and efficient service structure, the R&D team and technical personnel have gradually tried to apply big data technology to the 5G communication network and achieved certain results. In this context, the article takes the application of big data technology as a starting point, systematically discusses the application method of big data technology in 5G communication network, and studies the integration modeling and heterogeneous simulation of big data technology in 5G communication network based on deep learning. The simulation results show that the heterogeneous network improves big data by 6.6%. © 2022 IEEE

关键词： Heterogeneous networks

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modeling for Optimal Investment Strategy of Educational Donation 4

Modeling for Optimal Investment Strategy of Educational Dona...

引用

4th IEEE international conference on big data Analytics (ICBDA)

作者： Wang, Jinxiao Shao, Zhiquan Tsinghua Univ THU Beijing Peoples R China China Univ Polit Sci & Law CUPL Beijing Peoples R China

ISBN: (纸本)9781728112824

Nowadays, educational donation plays an important role in the development of education. Since the effectiveness of education donations is affected by many factors, this paper presents a model to find an optimal investment strategy by processing big data. First, a criterion of investment is established by using TOPSIS method. Based on the criterion, schools worth investing are selected through SVM method. After determining return of investment and prosperity index with method of Principal Component analysis and data Envelopment analysis, this model can allocate funds to invest institutions properly for the next five years, taking both indexes into consideration. Finally, this paper extends the model to make it more realistic.

关键词： educational donation optimal investment strategy model big data

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Polarized Topic modeling for User Characteristics in Online Discussion Community

Polarized Topic Modeling for User Characteristics in Online ...

引用

IEEE international conference on big data and Smart Computing (bigComp)

作者： Kim, Sung-Hwan Tak, Haesung Cho, Hwan-Gue Pusan Natl Univ Dept Elect & Comp Engn Busan South Korea

ISBN: (纸本)9781538677896

Topic modeling methods, such as latent Dirichlet allocation (LDA), are successfully applied in a number of computational linguistics applications. This paper presents a new approach to topic modeling within a new domain other than linguistic analysis. We present a pilot study where an LDA model is applied to an online community rather than the textual contents they produced using the idea that a user in an article is analogous to a word in a document within the context of the LDA model. We also propose a method for determining polarity using positive (+) and negative (-) signs regarding topics. As a result, each user has a topic score whose absolute value is equal to the topic distribution learned from topic modeling, and its sign indicates the polarity on that specific subject. We demonstrate the effectiveness of our proposed approach with experimental results, which provide opportunities to apply the LDA model to targets other than lexical elements.

关键词： LDA Online Community Topic modeling Polarity analysis

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Federated Multimodal big data Storage & Analytics Platform for Additive Manufacturing

Federated Multimodal Big Data Storage & Analytics Platform f...

引用

IEEE international conference on big data (big data)

作者： Aggour, Kareem S. Kumar, Vijay S. Cuddihy, Paul Williams, Jenny Weisenberg Gupta, Vipul Dial, Laura Hanlon, Tim Gambone, Justin Vinciquerra, Joseph GE Res AI Knowledge & Big Data Niskayuna NY 12309 USA GE Res Struct Mat Niskayuna NY 12309 USA GE Res Addit Technol Niskayuna NY 12309 USA

ISBN: (纸本)9781728108582

Additive technologies are expected to revolutionize manufacturing across almost every industry, but there is a sizable gap between the current state of the technology and the maturity required for it to achieve widespread adoption. Advanced analytics are required to improve the reliability and repeatability of additive manufacturing, and those analytics require data. Large volumes of multimodal data are generated and used throughout the additive manufacturing lifecycle, from material design to part design and simulation, part printing to post-processing and inspection. To capture and link that diverse big data together, we have designed and developed a federated multimodal big data storage and analytics platform comprised of three tiers-a distributed polyglot data storage and analysis tier with different repositories for different data structures, a metadata knowledge graph tier for modeling the data and their relationships across the various repositories, and a user interface tier for visualizing, exploring and invoking analytics on the data. The platform has been used to integrate a collection of previously disparate steps to optimize the process parameters used to build a new additive material, enabling materials scientists and other non-software experts to capture, visualize and analyze the requisite data through a single user interface.

关键词： additive manufacturing semantics knowledge graphs polyglot data storage Spark

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big data Logistics Inventory Control Model Based on Error Correction Model 11

Big Data Logistics Inventory Control Model Based on Error Co...

引用

11th international conference on Measuring Technology and Mechatronics Automation (ICMTMA)

作者： Pan, Canhui Kunming Met Coll Logist Engn & Management Fac Kunming 650033 Yunnan Peoples R China

ISBN: (纸本)9781728121659

As the basis for the production, planning and control in enterprises, inventory management provides an essential foundation for the production management and cost control of the enterprises. In this paper, the inventory in the big data logistics is controlled effectively based on the error correction model, which has implemented the construction of the big data logistics inventory control model. The significant contributions of the applications of big data in multiple aspects of the logistics linkage network to the development of the enterprise inventory management are summarized. In the summary of the advantages in the big data applications, the problems identified are studied and analyzed. The effect of the logistics inventory control put forward in this paper is analyzed through the inventory in the big data logistics. analysis of the feasibility and practicality is carried out. The research results show that the error correction model can be used to obtain relatively good modeling and the generalization capacity is also relatively strong.

关键词： big data Logistics Inventory Control Model Error Correction Model Nonlinear modeling

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2019 8th international conference on modeling simulation and Applied Optimization, ICMSAO 2019

2019 8th International Conference on Modeling Simulation and...

引用

8th international conference on modeling simulation and Applied Optimization, ICMSAO 2019

ISBN: (纸本)9781538676844

The proceedings contain 168 papers. The topics discussed include: a model order reduction technique based on balanced truncation method and artificial neural networks;a novel host readiness factor for energy-efficient VM consolidation in cloud data centers;multi-scale LPQ-DCT for image forgery detection;continuous non-invasive blood pressure monitoring device;3d-finite element analysis (FEA) of glass fiber reinforced polymer (GFRP) reinforced concrete members;a big data visualization layer meta-model proposition;and on the use of underground conduits as potential means for transmitting data.

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big data and simulation to Analyze Higher Education Sustainable Development 6

Big Data and Simulation to Analyze Higher Education Sustaina...

引用

6th Annual conference on Computational Science and Computational Intelligence (CSCI)

作者： Kurkovsky, Anatoly Univ Syst Georgia Georgia Gwinnett Coll Greater Atlanta GA 30043 USA

ISBN: (数字)9781728155845

ISBN: (纸本)9781728155845

Higher education institutions already accumulated enormous volumes of big data associated with student success, enrolment, professors, educational programs, educational computer systems, economics, etc., that potentially can be used for sustainable development analysis. However, their practical applications in higher education institutions are remained relatively rare because of complexity in the subject domain and lack of a methodological base to reuse some effective previously created models. This paper introduces an approach to incorporate big data into higher education sustainabiity analysis and reduce the complexity of the subject domain infrastructure by using a set of formalized systems. Within this approach, a simulation umbrella is used as a united methodological base to combine big data and sustainabiity analysis implementation. To illusfrate how the proposed approach works, a simulation case-study associated with a USA young fast-growing higher education institution included in the paper.

关键词： simulation approach big data sustainable development formalization higher education

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Search for K: Assessing Five Topic-modeling Approaches to 120,000 Canadian Articles

Search for K: Assessing Five Topic-Modeling Approaches to 12...

引用

IEEE international conference on big data (big data)

作者： Fu, Qiang Zhuang, Yufan Gu, Jiaxin Zhu, Yushu Qin, Huihui Guo, Xin Univ British Columbia Dept Sociol Vancouver BC Canada Columbia Univ Data Sci Inst New York NY USA Simon Fraser Univ Urban Studies Program Vancouver BC Canada Simon Fraser Univ Sch Publ Policy Vancouver BC Canada Hong Kong Polytech Univ Dept Appl Math Hong Kong Peoples R China

ISBN: (纸本)9781728108582

Topic modeling has been an important field in natural language processing (NLP) and recently witnessed great methodological advances. Yet, the development of topic modeling is still, if not increasingly, challenged by two critical issues. First, despite intense efforts toward nonparametric/post-training methods, the search for the optimal number of topics K remains a fundamental question in topic modeling and warrants input from domain experts. Second, with the development of more sophisticated models, topic modeling is now ironically been treated as a black box and it becomes increasingly difficult to tell how research findings are informed by data, model specifications, or inference algorithms. Based on about 120,000 newspaper articles retrieved from three major Canadian newspapers (Globe and Mail, Toronto Star, and National Post) since 1977, we employ five methods with different model specifications and inference algorithms (Latent Semantic analysis, Latent Dirichlet Allocation, Principal Component analysis, Factor analysis, Nonnegative Matrix Factorization) to identify discussion topics. The optimal topics are then assessed using three measures: coherence statistics, held-out likelihood (loss), and graph-based dimensionality selection. Mixed findings from this research complement advances in topic modeling and provide insights into the choice of optimal topics in social science research.

关键词： Topic modeling Natural Language Processing Social Science Optimal Number of Topics

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Research on Quantitative analysis of Security of Network Risk Based on big data

Research on Quantitative Analysis of Security of Network Ris...

引用

international conference on Robots and Intelligent System (ICRIS)

作者： Qian, Zhang Shaanxi Police Acad Xian 710043 Peoples R China

ISBN: (纸本)9781728126326

In big data environment, due to the rapid clustering and data forwarding of data in the multi-path transmission link layer, it is vulnerable to network virus implantation and intrusion. By quantifying the network risk security situation in big data environment, improve the ability to withstand risks. A quantitative analysis and prediction algorithm of network risk security situation in big data environment based on big data fuzzy C-means clustering and network intrusion information spectrum feature extraction is proposed. The quantitative analysis model of network risk security situation under the environment of big data is constructed. big data fuzzy C-means clustering algorithm is used to cluster and evaluate the statistical characteristic information data of network intrusion. The high-order spectrum characteristics of big data are analyzed quantitatively by extracting the security situation of network risk, and the quantitative assessment of network risk security situation and the detection of network intrusion are realized. The simulation results show that the algorithm has high accuracy in evaluating the situation of network risk security, and realizes the quantitative assessment and intrusion detection of network risk security situation in different scenarios, and improves the ability of the network to resist network intrusion under the environment of big data.

关键词： network security network risk security situation quantitative evaluation

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