Handbook of research on applied data science and artificial intelligence in business and industry:
"This book provides an overview of the concepts, tools and techniques behind the increasing field of Data Science and Artificial Intelligence, applied to business and industries"--
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :
IGI Global,
2021.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | "This book provides an overview of the concepts, tools and techniques behind the increasing field of Data Science and Artificial Intelligence, applied to business and industries"-- |
| Beschreibung: | 42 PDFs (2 volumes (653 pages)) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781799869863 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
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| 245 | 0 | 0 | |a Handbook of research on applied data science and artificial intelligence in business and industry |c Valentina Chkoniya, editor. |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : |b IGI Global, |c 2021. | |
| 300 | |a 42 PDFs (2 volumes (653 pages)) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Section 1. Strategy. Chapter 1. Port dada integration: opportunities for optimization and value creation ; Chapter 2. A software engineering perspective on building production-ready machine learning systems ; Chapter 3. Multivariate sustainability profile of global fortune 500 companies using GRI-G4 database ; Chapter 4. Examining the evolution of e-government development of nations through machine learning techniques ; Chapter 5. Artificial intelligence as driver for SME competitiveness ; Chapter 6. Big data is decision science: the case of COVID-19 vaccination ; Chapter 7. The future of advertising: influencing and predicting response through artificial intelligence, machine learning, and neuroscience -- Section 2. Action. Chapter 8. Retail customer native baskets creation: a must-do into measuring price indices ; Chapter 9. Studying customer experience and retention using applied data science and artificial intelligence ; Chapter 10. Using intelligent text analysis of online reviews to determine the main factors of restaurant value propositions ; Chapter 11. Time series forecasting in retail sales using LSTM and prophet ; Chapter 12. General model for metrics calculation and behavior prediction in the manufacturing industry: an automated machine learning approach ; Chapter 13. AI meaning and applications in the consumer sector of retailing, hospitality, and tourism ; Chapter 14. Key factors in the process of acceptance and implementation of artificial intelligence in the hotel sector ; Chapter 15. Peruvian consumer responses to the use of technologies in the context of COVID-19 ; Chapter 16. Artificial intelligence in marketing: a review of consumer-AI interactions ; Chapter 17. When luxury vinous-concept hotel meets premium wine brands: an exploratory study on co-branding ; Chapter 18. Data analysis in the shipping industry: eShip case study problem statement ; Chapter 19. Question answering chatbot using memory networks ; Chapter 20. Comparison of parametric and non-parametric methods to analyse the data gathered by a likert-type scale ; Chapter 21. Latent fingerprint enhancement based on EDTV model ; Chapter 22. The business, societal, and enterprise architecture framework: an artificial intelligence-, data sciences-, and big data-based approach ; Chapter 23. The effect of population, public investments, and economic growth on regional renewable energy consumption in Turkey: dynamic panel data analysis -- Section 3. Reflection. Chapter 24. Education for the digital industry: opportunities and challenges of experience-based expertise and open innovation ; Chapter 25. The contribution of data science applied to customer relationship management: a systematic literature review ; Chapter 26. Data science in economics and business: roots and applications ; Chapter 27. A historical review of immersive storytelling technologies: new uses of AI, data science, qnd user experience in virtual worlds ; Chapter 28. Artificial intelligences are subsets of human beings, mainly in fictions and films: challenges and opportunities ; Chapter 29. Towards ethical neuromarketing 2.0 based on artificial intelligence ; Chapter 30. Responsible machine learning for ethical artificial intelligence in business and industry. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "This book provides an overview of the concepts, tools and techniques behind the increasing field of Data Science and Artificial Intelligence, applied to business and industries"-- |c Provided by publisher. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 08/14/2021). | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Business |x Technological innovations. | |
| 650 | 0 | |a Databases. | |
| 650 | 7 | |a Artificial intelligence. |2 fast | |
| 650 | 7 | |a Business |x Technological innovations. |2 fast | |
| 650 | 7 | |a Databases. |2 fast | |
| 700 | 1 | |a Chkoniya, Valentina |d 1977- |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
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| contents | Section 1. Strategy. Chapter 1. Port dada integration: opportunities for optimization and value creation ; Chapter 2. A software engineering perspective on building production-ready machine learning systems ; Chapter 3. Multivariate sustainability profile of global fortune 500 companies using GRI-G4 database ; Chapter 4. Examining the evolution of e-government development of nations through machine learning techniques ; Chapter 5. Artificial intelligence as driver for SME competitiveness ; Chapter 6. Big data is decision science: the case of COVID-19 vaccination ; Chapter 7. The future of advertising: influencing and predicting response through artificial intelligence, machine learning, and neuroscience -- Section 2. Action. Chapter 8. Retail customer native baskets creation: a must-do into measuring price indices ; Chapter 9. Studying customer experience and retention using applied data science and artificial intelligence ; Chapter 10. Using intelligent text analysis of online reviews to determine the main factors of restaurant value propositions ; Chapter 11. Time series forecasting in retail sales using LSTM and prophet ; Chapter 12. General model for metrics calculation and behavior prediction in the manufacturing industry: an automated machine learning approach ; Chapter 13. AI meaning and applications in the consumer sector of retailing, hospitality, and tourism ; Chapter 14. Key factors in the process of acceptance and implementation of artificial intelligence in the hotel sector ; Chapter 15. Peruvian consumer responses to the use of technologies in the context of COVID-19 ; Chapter 16. Artificial intelligence in marketing: a review of consumer-AI interactions ; Chapter 17. When luxury vinous-concept hotel meets premium wine brands: an exploratory study on co-branding ; Chapter 18. Data analysis in the shipping industry: eShip case study problem statement ; Chapter 19. Question answering chatbot using memory networks ; Chapter 20. Comparison of parametric and non-parametric methods to analyse the data gathered by a likert-type scale ; Chapter 21. Latent fingerprint enhancement based on EDTV model ; Chapter 22. The business, societal, and enterprise architecture framework: an artificial intelligence-, data sciences-, and big data-based approach ; Chapter 23. The effect of population, public investments, and economic growth on regional renewable energy consumption in Turkey: dynamic panel data analysis -- Section 3. Reflection. Chapter 24. Education for the digital industry: opportunities and challenges of experience-based expertise and open innovation ; Chapter 25. The contribution of data science applied to customer relationship management: a systematic literature review ; Chapter 26. Data science in economics and business: roots and applications ; Chapter 27. A historical review of immersive storytelling technologies: new uses of AI, data science, qnd user experience in virtual worlds ; Chapter 28. Artificial intelligences are subsets of human beings, mainly in fictions and films: challenges and opportunities ; Chapter 29. Towards ethical neuromarketing 2.0 based on artificial intelligence ; Chapter 30. Responsible machine learning for ethical artificial intelligence in business and industry. |
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| illustrated | Not Illustrated |
| indexdate | 2024-11-26T14:51:57Z |
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| isbn | 9781799869863 |
| language | English |
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| spelling | Handbook of research on applied data science and artificial intelligence in business and industry Valentina Chkoniya, editor. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, 2021. 42 PDFs (2 volumes (653 pages)) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Section 1. Strategy. Chapter 1. Port dada integration: opportunities for optimization and value creation ; Chapter 2. A software engineering perspective on building production-ready machine learning systems ; Chapter 3. Multivariate sustainability profile of global fortune 500 companies using GRI-G4 database ; Chapter 4. Examining the evolution of e-government development of nations through machine learning techniques ; Chapter 5. Artificial intelligence as driver for SME competitiveness ; Chapter 6. Big data is decision science: the case of COVID-19 vaccination ; Chapter 7. The future of advertising: influencing and predicting response through artificial intelligence, machine learning, and neuroscience -- Section 2. Action. Chapter 8. Retail customer native baskets creation: a must-do into measuring price indices ; Chapter 9. Studying customer experience and retention using applied data science and artificial intelligence ; Chapter 10. Using intelligent text analysis of online reviews to determine the main factors of restaurant value propositions ; Chapter 11. Time series forecasting in retail sales using LSTM and prophet ; Chapter 12. General model for metrics calculation and behavior prediction in the manufacturing industry: an automated machine learning approach ; Chapter 13. AI meaning and applications in the consumer sector of retailing, hospitality, and tourism ; Chapter 14. Key factors in the process of acceptance and implementation of artificial intelligence in the hotel sector ; Chapter 15. Peruvian consumer responses to the use of technologies in the context of COVID-19 ; Chapter 16. Artificial intelligence in marketing: a review of consumer-AI interactions ; Chapter 17. When luxury vinous-concept hotel meets premium wine brands: an exploratory study on co-branding ; Chapter 18. Data analysis in the shipping industry: eShip case study problem statement ; Chapter 19. Question answering chatbot using memory networks ; Chapter 20. Comparison of parametric and non-parametric methods to analyse the data gathered by a likert-type scale ; Chapter 21. Latent fingerprint enhancement based on EDTV model ; Chapter 22. The business, societal, and enterprise architecture framework: an artificial intelligence-, data sciences-, and big data-based approach ; Chapter 23. The effect of population, public investments, and economic growth on regional renewable energy consumption in Turkey: dynamic panel data analysis -- Section 3. Reflection. Chapter 24. Education for the digital industry: opportunities and challenges of experience-based expertise and open innovation ; Chapter 25. The contribution of data science applied to customer relationship management: a systematic literature review ; Chapter 26. Data science in economics and business: roots and applications ; Chapter 27. A historical review of immersive storytelling technologies: new uses of AI, data science, qnd user experience in virtual worlds ; Chapter 28. Artificial intelligences are subsets of human beings, mainly in fictions and films: challenges and opportunities ; Chapter 29. Towards ethical neuromarketing 2.0 based on artificial intelligence ; Chapter 30. Responsible machine learning for ethical artificial intelligence in business and industry. Restricted to subscribers or individual electronic text purchasers. "This book provides an overview of the concepts, tools and techniques behind the increasing field of Data Science and Artificial Intelligence, applied to business and industries"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 08/14/2021). Artificial intelligence. Business Technological innovations. Databases. Artificial intelligence. fast Business Technological innovations. fast Databases. fast Chkoniya, Valentina 1977- editor. IGI Global, publisher. (Original) (DLC)2020058396 Print version: 1799869857 9781799869856 (DLC) 2020058396 FWS01 ZDB-98-IGB FWS_PDA_IGB http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-6985-6 Volltext |
| spellingShingle | Handbook of research on applied data science and artificial intelligence in business and industry Section 1. Strategy. Chapter 1. Port dada integration: opportunities for optimization and value creation ; Chapter 2. A software engineering perspective on building production-ready machine learning systems ; Chapter 3. Multivariate sustainability profile of global fortune 500 companies using GRI-G4 database ; Chapter 4. Examining the evolution of e-government development of nations through machine learning techniques ; Chapter 5. Artificial intelligence as driver for SME competitiveness ; Chapter 6. Big data is decision science: the case of COVID-19 vaccination ; Chapter 7. The future of advertising: influencing and predicting response through artificial intelligence, machine learning, and neuroscience -- Section 2. Action. Chapter 8. Retail customer native baskets creation: a must-do into measuring price indices ; Chapter 9. Studying customer experience and retention using applied data science and artificial intelligence ; Chapter 10. Using intelligent text analysis of online reviews to determine the main factors of restaurant value propositions ; Chapter 11. Time series forecasting in retail sales using LSTM and prophet ; Chapter 12. General model for metrics calculation and behavior prediction in the manufacturing industry: an automated machine learning approach ; Chapter 13. AI meaning and applications in the consumer sector of retailing, hospitality, and tourism ; Chapter 14. Key factors in the process of acceptance and implementation of artificial intelligence in the hotel sector ; Chapter 15. Peruvian consumer responses to the use of technologies in the context of COVID-19 ; Chapter 16. Artificial intelligence in marketing: a review of consumer-AI interactions ; Chapter 17. When luxury vinous-concept hotel meets premium wine brands: an exploratory study on co-branding ; Chapter 18. Data analysis in the shipping industry: eShip case study problem statement ; Chapter 19. Question answering chatbot using memory networks ; Chapter 20. Comparison of parametric and non-parametric methods to analyse the data gathered by a likert-type scale ; Chapter 21. Latent fingerprint enhancement based on EDTV model ; Chapter 22. The business, societal, and enterprise architecture framework: an artificial intelligence-, data sciences-, and big data-based approach ; Chapter 23. The effect of population, public investments, and economic growth on regional renewable energy consumption in Turkey: dynamic panel data analysis -- Section 3. Reflection. Chapter 24. Education for the digital industry: opportunities and challenges of experience-based expertise and open innovation ; Chapter 25. The contribution of data science applied to customer relationship management: a systematic literature review ; Chapter 26. Data science in economics and business: roots and applications ; Chapter 27. A historical review of immersive storytelling technologies: new uses of AI, data science, qnd user experience in virtual worlds ; Chapter 28. Artificial intelligences are subsets of human beings, mainly in fictions and films: challenges and opportunities ; Chapter 29. Towards ethical neuromarketing 2.0 based on artificial intelligence ; Chapter 30. Responsible machine learning for ethical artificial intelligence in business and industry. Artificial intelligence. Business Technological innovations. Databases. Artificial intelligence. fast Business Technological innovations. fast Databases. fast |
| title | Handbook of research on applied data science and artificial intelligence in business and industry |
| title_auth | Handbook of research on applied data science and artificial intelligence in business and industry |
| title_exact_search | Handbook of research on applied data science and artificial intelligence in business and industry |
| title_full | Handbook of research on applied data science and artificial intelligence in business and industry Valentina Chkoniya, editor. |
| title_fullStr | Handbook of research on applied data science and artificial intelligence in business and industry Valentina Chkoniya, editor. |
| title_full_unstemmed | Handbook of research on applied data science and artificial intelligence in business and industry Valentina Chkoniya, editor. |
| title_short | Handbook of research on applied data science and artificial intelligence in business and industry |
| title_sort | handbook of research on applied data science and artificial intelligence in business and industry |
| topic | Artificial intelligence. Business Technological innovations. Databases. Artificial intelligence. fast Business Technological innovations. fast Databases. fast |
| topic_facet | Artificial intelligence. Business Technological innovations. Databases. |
| url | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-6985-6 |
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