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检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

共 1353 条记录，以下是31-40 订阅

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Utilizing an Airline data Warehouse for Website data Analytics: A Conceptual Design

Utilizing an Airline Data Warehouse for Website Data Analyti...

引用

international conference on big data intelligence and computing, datacom 2022

作者： Kumar, Ravnesh Kumar, Kunal Department of Computer Science and Mathematics The University of Fiji Lautoka Fiji

ISBN: (纸本)9789819922321

As a result of the Covid-19 outbreak, airlines are focusing more on online booking engines, which require airlines to segment clients, target personalized offers, and monitor channel performance, advertising spend, goal conversion, and campaign effectiveness using web analytics data. To accommodate all of these aspects, as well as quick responses to current and future demands, enhanced planning, and alignment with corporate decision-making, a data warehouse is required. This study will illustrate how to integrate website data into a data warehouse as well as its data model using the snowflake schema. A thorough case study on understanding airline digital booking engine data at different stages of its lifecycle through a data warehouse architecture using the four-step dimensional modelling approach, allowing smart revenue management for airlines, provided more clarification of the strategy. This post will mostly benefit the airline’s digital team, data warehouse and database administrators, digital analysts, revenue management team, and functional segments throughout the organization that use digital passenger-booking inputs to make strategic choices. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Websites

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Latent Inter-relation Augment between Crimes and Criminals using Factorization Machines

Latent Inter-relation Augment between Crimes and Criminals u...

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

作者： Yeon, Jeongheun Jhee, Jong Ho Shin, Hyunjung Ajou Univ Dept Artificial Intelligence Suwon South Korea Ajou Univ Sch Med Suwon South Korea Ajou Univ Ind Engn Dept Artificial Intelligence Suwon South Korea

ISBN: (纸本)9781665475785

In the process of criminal investigation, it is a very important to understand the relationship between the case and related persons. It is difficult and cumbersome to figure out every time in the fragmented cases. To leverage this relational information, Graph-based machine learning-based approaches are being studied recently and natural in criminal. If you construct a crime network composed of criminal cases and related persons, a more systematic, in-depth, and broader investigation is possible by utilizing connection information. However, since previously known connection between cases and persons is within the range of a single case, it is very sparse, so it is hard to beyond a single case. In this study, we propose a method to infer the latent relationship using this rare case-person connection information and augment the existing network. Through this, it was confirmed that the augmented crime network can make maximum use of information beyond a single case, and the network expressive power is greatly improved for cases where single-case information was initially small. To verify the augmentation performance, it was verified by applying it to the actual crime data collected by the Korean National Police Agency.

关键词： factorization machines inter-relation augmentation crime network graph-based semi-supervised learning heterogeneous network

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Integrating Multimodal Geospatiotemporal data for Societal, Economic, and Environmental (SEE) Analysis of Large Agricultural Systems

Integrating Multimodal Geospatiotemporal Data for Societal, ...

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2024 IEEE international conference on big data, bigdata 2024

作者： Akanbi, Olatunde D. Li, Jiaqi Mandayam, Vibha Nihar, Arafath Wu, Yinghui Bruckman, Laura S. Yarus, Jeffrey M. Barcelos, Erika I. French, Roger H. Sdle Department of Material Science and Engineering Case Western Reserve University ClevelandOH United States Department of Material Science and Engineering Case Western Reserve University ClevelandOH United States Department of Computer and Data Science Case Western Reserve University ClevelandOH United States United States

ISBN: (纸本)9798350362480

关键词： Agricultural economics

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SPath: An Energy-Efficient DAG Task Offloading Scheme with Space-Ground Cooperative computing

SPath: An Energy-Efficient DAG Task Offloading Scheme with ...

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international conference on big data intelligence and computing, datacom 2022

作者： Zhao, Tianqi Zhao, Mingyue Shi, Yue Zheng, Kuangyu Department of Mathematics and Theories Peng Cheng Laboratory Shenzhen China School of Electronic and Information Engineering Beihang University Beijing China

ISBN: (纸本)9789819922321

The fast improvement of satellites in both computation ability and numbers in the network, makes them possible to form as promising edge computing nodes for space-ground cooperative computing. These satellite edges are especially helpful to cover IoT terminals in remote areas (e.g. deserts, forests, and oceans) who have both limited computation and battery resource, as well as short time deadlines. However, the mobility and flexibility of satellites, and the dependence between subtasks of terminal DAG (Directed Acyclic Graph) tasks, pose new challenges to the cooperative offloading scenarios. Moreover, the energy supply for both the ground terminals and the edge satellites are very constrained, and are demanded to be optimized for longer services. To solve this problem, we propose SPath, an energy-efficient satellite-ground cooperative offloading scheme, which can reduce the energy consumption and latency of DAG tasks. Moreover, it transforms the offload performance optimization problem into a shortest path problem for a more direct solution. The simulation results with real StarLink satellite movement data show that SPath manages to reduce the energy consumption of DAG tasks by 40.1% and the delay by 39.5% over the exited methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Satellites

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big data Real-Time Processing Architecture Based on Hadoop

Big Data Real-Time Processing Architecture Based on Hadoop

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2022 international conference on Artificial intelligence, Virtual Reality, and Visualization, AIVRV 2022

作者： Cao, Yong Chongqing City Vocational College Chongqing Yongchuan402160 China

ISBN: (纸本)9781510662988

The data generated in the Internet age is increasing exponentially. Sometimes such a huge amount of data cannot be processed in time, and people cannot dig out useful information from it. In order to realize the efficient processing of massive data, this paper develops a big data real-time processing architecture based on the Hadoop platform, uses HBase as the database, and combines the C# programming language and the MapReduce programming mode to design a big data processing system, so that users can view and upload data through mobile devices. The data processing results of the cloud computing center. The performance test of MapReduce and various functional modules of the big data processing architecture is carried out. The test results show that MapReduce has certain advantages in processing big data, and the data processing time of each functional module increases with the increase of data volume. © 2023 SPIE. All rights reserved.

关键词： data handling

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Optimizing data Stream Throughput for Real-Time Applications

Optimizing Data Stream Throughput for Real-Time Applications

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international conference on big data intelligence and computing, datacom 2022

作者： Amilineni, Kusuma Hsu, Po-Yen Hsu, Ching-Hsien Baghban, Hojjat Chang, Wen-Thong Eshwarappa, Nithin Melala Department of Computer Science and Information Engineering Asia University Taichung Taiwan Department of Mechanical Engineering National Chung Cheng University Chiayi Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Chiayi Taiwan

ISBN: (纸本)9789819922321

Many problems, like recommendation services, website log activities, commit logs, and event sourcing services, are often very high volume and high velocity as many activity messages are generated. Various cloud vendors offer services for building message transport and processing pipelines. We present the Apache Kafka optimization process for using Kafka as a messaging system in high throughput and low latency systems. Experiments are conducted with various configurations for observing their effects on performance metrics. The performance, Durability, and reliability trade-offs of Apache Kafka are presented for various data rates, resource utilization, and configurations on how to utilize resources more economically and choose the best Kafka configuration for use cases. This research presents by tuning configuration parameters leveraged throughput by 19%. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Economic and social effects

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The Innovation Mode and Path Analysis of English Education Based on big data

The Innovation Mode and Path Analysis of English Education B...

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2022 international conference on Mathematics, Modeling, and Computer Science, MMCS 2022

作者： Chen, Lihui Jimei University Chengyi College Xiamen China

ISBN: (纸本)9781510664593

In the context of the era of big data, the education field has built a new intelligent experience system according to its own business needs, which can not only accelerate the development of intelligent education, but also continuously expand the application scope of big data technology. From the perspective of modern education, it is helpful to construct a good big data education environment for teachers and students by constructing a big data intelligent education system based on user roles and role needs and properly handling educational guidance and management of various disciplines. Therefore, on the basis of understanding the development status of big data technology, this paper deeply discusses the innovation mode and specific path of English education in the context of big data according to the technical concepts of artificial intelligence and cloud computing. © 2023 SPIE.

关键词： big data

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big data Visualization Tools, Challenges and Web Search Popularity - An Update till Today

Big Data Visualization Tools, Challenges and Web Search Popu...

引用

international conference on big data intelligence and computing, datacom 2022

作者： Kumar, Anal Shawkat Ali, A.B.M. Fiji National University Nadi Fiji The University of Fiji Lautoka Fiji

ISBN: (纸本)9789819922321

In today’s culture, when everything is recorded digitally, from online surfing habits to medical records, individuals produce and consume petabytes of data every day. Every element of life will undergo a change thanks to big data. However, just processing and interpreting the data is insufficient;the human brain is more likely to find patterns when the data is shown visually. data analytics and visualization are crucial decision-making tools in many different businesses. Additionally, it creates new opportunities for visualization, reflecting imaginative problem-solving with the aid of large amounts of data. It might be challenging to see such a large amount of data in real time or in a static manner. In this paper, the authors discuss the importance of big data visualization, the issues, and the use of several large data visualization techniques. The enormous data mine cannot become a gold mine until sophisticated and intelligent analytics algorithms are applied to it, and the findings of the analytical process are presented in an effective, efficient, and stunning way. Unsurprisingly, a plethora of big data visualization tools and approaches have emerged in the last few years, both as independent apps or plugins for data management systems and as a component of data management systems. The dataset obtained from Google Trends is prepared and experimented upon to visualize the Web search trends for Microsoft Power BI, Tableau, Qliikview, Infogram and Google Charts. Through this data visualization experiment various insights have been obtained that illustrates how sharply Power BI is gaining popularity as compared to rather modest trend of Tableau and other data Visualization tools. Furthermore, the authors provide more insight on top listed countries searching for various data Visualization tools and categorizing various data Visualization tools of interest based of geographical locations. On account of these issues, this article provides an overview of the most pop

关键词： data visualization

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State-of-the-art Review on Intelligent computing-based Privacy Preservation Technologies for Power Internet of Things 24

State-of-the-art Review on Intelligent Computing-based Priva...

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6th international conference on big data Engineering (BDE)

作者： Huang, Hao Chen, Wentao Fang, Weidong Li, Zhiqi Chen, Wei Ip, Wai-Hung Yung, Kai-Leung Hubei Univ Fac Microelect Micronanoelect Mat & Devices Wuhan 430062 Hubei Peoples R China State Grid Xinjiang Co Ltd Elect Power Res Inst Urumqi 830011 Peoples R China Chinese Acad Sci Shanghai Inst Microsyst & Informat Technol Sci & Technol Microsyst Lab Shanghai 201899 Peoples R China Univ Chinese Acad Sci Sch Elect Elect & Commun Engn Beijing 100049 Peoples R China Shanghai Res & Dev Ctr Micronano Elect Shanghai 201210 Peoples R China China Univ Min & Technol Sch Comp Sci & Technol Xuzhou 221116 Jiangsu Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong 100872 Peoples R China

ISBN: (纸本)9798400717857

In the power Internet of Things (power IoTs), the connections between many electric power equipments and modules with sensing and communication functions are facing the security challenge and privacy disclosure risk. Artificial intelligence (AI),especially intelligent computing, is widely acknowledged as an effective approach for preserving privacy. However, there remains a notable gap for a comprehensive review paper focused on intelligent computing-based privacy preservation technologies in power IoTs. Therefore, conducting a state-of-the-art review on this subject has become imperative. In this paper,the recent relevant research works are aimed to compare and analyze. Moreover,the privacy preservation schemes based on AI are summarized. Lastly, the conclusions are provided.

关键词： Power Internet of Things Artificial intelligence Privacy Preservation Security Intelligent computing

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Application of AI, big data and Cloud computing Technology in Smart Factories 6

Application of AI, Big Data and Cloud Computing Technology i...

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6th international conference on Artificial intelligence and big data, ICAIBD 2023

作者： Yin, Yong Zhao, Minghui Changshu Tiandi Coal Mining Equipment Co. Ltd Changshu China School of Electronics and Information Engineering Tongji University Shanghai China China Coal Technology & Engineering Group Shanghai Co. Ltd. Shanghai China

ISBN: (纸本)9781665491259

AI, big data and cloud computing technology are used as a tool to extend intelligence and improve our ability to understand and transform the world, resulting in a new AI economic form. In recent years, the combination of artificial intelligence and industrial manufacturing is increasingly attracting attention. The integration of multiple information and the injection of high-tech and intelligent technologies will greatly promote the transformation from traditional manufacturing to new smart factories. This paper analyzes the basic concepts and characteristics of AI, big data and cloud computing, as well as the characteristics and technical framework construction of smart factories. Given the characteristics of manufacturing enterprises and the need for in-depth application of information systems, it describes how AI, big data and cloud computing technologies are applied in smart factories through practical application scenarios. © 2023 IEEE.

关键词： big data

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