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Handbook of research on driving socioeconomic development with big data [electronic resource] / Zhaohao Sun.

  • 其他作者:
  • 其他題名:
    • Research on driving socioeconomic development with big data
    • Advances in data mining and database management (ADMDM) book series.
  • 出版: Hershey, Pennsylvania : IGI Global 2023.
  • 叢書名: Advances in data mining and database management (ADMDM) book series
  • 主題: Information technology--Economic aspects. , Big data--Economic aspects. , Sustainable development. , Economic development. , Electronic books.
  • ISBN: 9781668459614 (electronic bk.) 、 1668459590 、 9781668459591
  • URL: 點擊此處查看電子書
    點擊此處查看電子書
  • 一般註:Includes bibliographical references and index. Section 1. Theories of driving socioeconomic development with big data. Chapter 1. Big data-driven socioeconomic development: an interdisciplinary approach ; Chapter 2. An empirical illustration of how socioeconomic stakeholders canleverage AI and big data ; Chapter 3. Promises and challenges relating to machine learning techniques to predict areas at risk of desertification: a state-of-the-art review ; Chapter 4. Corporate social reasonability roles in artificial intelligence and big data analytics in management -- Section 2. Technologies for driving socioeconomic development with big data. Chapter 5. Enhancing airport business services using big data analytics ; Chapter 6. Authentication-based hybridapproach using RSA for data security in the cloud ; Chapter 7. Vendor-managed inventory and its support technologies: an inside look at supplier and customer relationships ; Chapter 8. A case-based reasoning system-based random forest for classification: a systematic literature review ; Chapter 9. Human resources development for the use of big data analytics in the customer business of German banks ; Chapter 10. A formulaic approach for selecting big data analytics tools fororganizational purposes -- Section 3. Applications of driving socioeconomic development with big data. Chapter 11. COVID-19 fake news on Twitter: a statistical and sentimental analysis ; Chapter 12. Technical and resilience aspects of agilitysupply chain management policies and practices: suggested approaches ; Chapter 13. Social media analytics for non-governmental organizations: a case study of Hong Kong next generation arts ; Chapter 14. Assessment of land administrationin Pakistan and the potential role of volunteered geographic information ; Chapter 15. How important is it to be beautiful?: the effect of beauty premium on wages ; Chapter 16. Journal editors can benefit from the archived data analysis: two case studies. 112年度臺灣學術電子書暨資料庫聯盟採購
  • 讀者標籤:
  • 引用連結:
  • 系統號: 000306474 | 機讀編目格式

館藏資訊

Socioeconomic development has drawn increasing attention in academia, industries, and governments. The relationship between big data and its technologies and socioeconomic development has drawn certain attention in academia. Socioeconomic development depends not only on big data, but also on big data technologies. However, the relationship between big data and socioeconomic development is not adequately covered in current research. The Handbook of Research on Driving Socioeconomic Development With Big Data provides an original and innovative understanding of and insight into how the proposed theories, technologies, and methodologies of big data can improve socioeconomic development and sustainable development in terms of business and services, healthcare, the internet of everything, sharing economy, and more. Covering topics such as corporate social responsibility, management applications, and process mining, this major reference work is an excellent resource for data scientists, business leaders and executives, IT professionals, government officials, economists, sociologists, librarians, students, researchers, and academicians.

摘要註

"This book explores novel big data theories, algorithms, technologies, methodologies, and applications for driving socio-economic development and sustainable development, highlighting perspectives in terms of theories, technologies,and applications as well as big data and its technologies to explore socio-economic development"--

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