國立高雄大學圖資館 |

Encyclopedia of data science and machine learning

Record Type:	Electronic resources : Monograph/item
Title/Author:	Encyclopedia of data science and machine learningJohn Wang, editor.
other author:	Wang, John,
Published:	Hershey, Pennsylvania :IGI Global,2023.
Description:	1 online resource (5 volumes (3143 p.))
Subject:	Big data.
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-9220-5
ISBN:	9781799892212 (electronic bk.)

Encyclopedia of data science and machine learning
Encyclopedia of data science and machine learning[electronic resource] /John Wang, editor. - Hershey, Pennsylvania :IGI Global,2023. - 1 online resource (5 volumes (3143 p.))

Includes bibliographical references and index.

Volume I. Section 1. Accounting analytics. Chapter 1. Auditor change prediction using data mining and audit reports ; Chapter 2. Volatility of semiconductor companies -- Section 2. Approximation methods. Chapter 3. Use of AI in predicting trends in vegetation dynamics in Africa -- Section 3. Autonomous learning systems. Chapter 4. Data science for industry 4.0 -- Section 4. Big data applications. Chapter 5. A patient-centered data-driven analysis of epidural anesthesia ; Chapter 6. Analysis of big data ; Chapter 7. Big data analytics in e-governance and other aspects of society ; Chapter 8. Big data and Islamic finance ; Chapter 9. Big data helps for non-pharmacological disease control measures of COVID-19 ; Chapter 10. Big data mining and analytics with mapreduce ; Chapter 11. Big data technologies and pharmaceutical manufacturing ; Chapter 12. Data warehouse with OLAP technology for the tourism industry ; Chapter 13. Defect detection inmanufacturing via machine learning algorithms ; Chapter 14. Diving into the rabbit hole: understanding delegation of decisions ; Chapter 15. Importance of AI and ML towards smart sensor network utility enhancement ; Chapter 16. Leveraging wi-fi big data streams to support COVID-19 contact tracing ; Chapter 17. Machine learning in the catering industry ; Chapter 18. Speedy management of data using mapreduce approach ; Chapter 19. Storage and query processing architectures forRDF data ; Chapter 20. Virtual singers empowered by machine learning -- Section 5. Big data as a service. Chapter 21. Analyzing U.S. maritime trade and COVID-19 impact using machine learning ; Chapter 22. NEW ARP: data-driven academia resource planning for CAS researchers -- Section 6. Big data systems and tools. Chapter 23. A meta-analytical review of deep learning prediction models for big data ; Chapter 24. Cluster analysis as a decision-making tool ; Chapter 25. Data lakes; Chapter 26. Datafied modelling of self-disclosure in online health communication ; Chapter 27. Extending graph databases with relational concepts ; Chapter 28. Free text to standardized concepts to clinical decisions ; Chapter 29. Internet search behavior in times of COVID-19 lockdown and opening ; Chapter 30. Interparadigmatic perspectives are supported by data structures ; Chapter 31. Oracle 19c's multitenant container architecture and big data ; Chapter 32. Trending bigdata tools for industrial data analytics -- Section 7. Business intelligence. Chapter 33. Artificial intelligence, consumers, and the experience economy ; Chapter 34. Business intelligence applied to tourism ; Chapter 35. Customer churn reduction based on action rules and collaboration ; Chapter 36. How artificial intelligence is impacting marketing? -- Volume II. Chapter 37. Interactive workbook on science communication ; Chapter 38. International trade, economic growth, and Turkey ; Chapter 39. Machine learning and exploratory data analysis in cross-sell insurance ; Chapter 40. Tracking buying behavior by analyzing electronic word of mouth ; Chapter 41. Web service in knowledge management for global softwaredevelopment -- Section 8. Causal analysis. Chapter 42. Hedonic hunger and obesity -- Section 9. Chaos control, modeling, and engineering. Chapter 43. Vapor compression refrigeration system data-based comprehensive model -- Section 10. Cloud infrastructure. Chapter 44. Cryptic algorithms: hiding sensitive information in cloud computing ; Chapter 45. Review on reliability and energy-efficiency issues in cloud computing -- Section 11. Cognitive science. Chapter 46. Abductive s

"This book examines current, state-of-the-art research in the areas of data science, machine learning, data mining, optimization, artificial intelligence, statistics, and the interactions, linkages, and applications of knowledge-based business with information systems"--

ISBN: 9781799892212 (electronic bk.)Subjects--Topical Terms:

609582
Big data.
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: QA76.9.B45 / E54 2023e

Dewey Class. No.: 005.7

Encyclopedia of data science and machine learning
LDR:08345nmm a2200265 a 4500 001 644232
006 m d
007 cr nn muauu
008 231206s2023 pau fob 001 0 eng d
020 $a 9781799892212 (electronic bk.)
020 $a 9781799892205
035 $a (CaBNVSL)slc00004015
035 $a (OCoLC)1369704434
035 $a 00276507
040 $a CaBNVSL $b eng $c CaBNVSL $d CaBNVSL
041 0 $a eng
050 4 $a QA76.9.B45 $b E54 2023e
082 0 4 $a 005.7 $2 23
245 0 0 $a Encyclopedia of data science and machine learning $h [electronic resource] / $c John Wang, editor.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2023.
300 $a 1 online resource (5 volumes (3143 p.))
504 $a Includes bibliographical references and index.
505 0 $a Volume I. Section 1. Accounting analytics. Chapter 1. Auditor change prediction using data mining and audit reports ; Chapter 2. Volatility of semiconductor companies -- Section 2. Approximation methods. Chapter 3. Use of AI in predicting trends in vegetation dynamics in Africa -- Section 3. Autonomous learning systems. Chapter 4. Data science for industry 4.0 -- Section 4. Big data applications. Chapter 5. A patient-centered data-driven analysis of epidural anesthesia ; Chapter 6. Analysis of big data ; Chapter 7. Big data analytics in e-governance and other aspects of society ; Chapter 8. Big data and Islamic finance ; Chapter 9. Big data helps for non-pharmacological disease control measures of COVID-19 ; Chapter 10. Big data mining and analytics with mapreduce ; Chapter 11. Big data technologies and pharmaceutical manufacturing ; Chapter 12. Data warehouse with OLAP technology for the tourism industry ; Chapter 13. Defect detection inmanufacturing via machine learning algorithms ; Chapter 14. Diving into the rabbit hole: understanding delegation of decisions ; Chapter 15. Importance of AI and ML towards smart sensor network utility enhancement ; Chapter 16. Leveraging wi-fi big data streams to support COVID-19 contact tracing ; Chapter 17. Machine learning in the catering industry ; Chapter 18. Speedy management of data using mapreduce approach ; Chapter 19. Storage and query processing architectures forRDF data ; Chapter 20. Virtual singers empowered by machine learning -- Section 5. Big data as a service. Chapter 21. Analyzing U.S. maritime trade and COVID-19 impact using machine learning ; Chapter 22. NEW ARP: data-driven academia resource planning for CAS researchers -- Section 6. Big data systems and tools. Chapter 23. A meta-analytical review of deep learning prediction models for big data ; Chapter 24. Cluster analysis as a decision-making tool ; Chapter 25. Data lakes; Chapter 26. Datafied modelling of self-disclosure in online health communication ; Chapter 27. Extending graph databases with relational concepts ; Chapter 28. Free text to standardized concepts to clinical decisions ; Chapter 29. Internet search behavior in times of COVID-19 lockdown and opening ; Chapter 30. Interparadigmatic perspectives are supported by data structures ; Chapter 31. Oracle 19c's multitenant container architecture and big data ; Chapter 32. Trending bigdata tools for industrial data analytics -- Section 7. Business intelligence. Chapter 33. Artificial intelligence, consumers, and the experience economy ; Chapter 34. Business intelligence applied to tourism ; Chapter 35. Customer churn reduction based on action rules and collaboration ; Chapter 36. How artificial intelligence is impacting marketing? -- Volume II. Chapter 37. Interactive workbook on science communication ; Chapter 38. International trade, economic growth, and Turkey ; Chapter 39. Machine learning and exploratory data analysis in cross-sell insurance ; Chapter 40. Tracking buying behavior by analyzing electronic word of mouth ; Chapter 41. Web service in knowledge management for global softwaredevelopment -- Section 8. Causal analysis. Chapter 42. Hedonic hunger and obesity -- Section 9. Chaos control, modeling, and engineering. Chapter 43. Vapor compression refrigeration system data-based comprehensive model -- Section 10. Cloud infrastructure. Chapter 44. Cryptic algorithms: hiding sensitive information in cloud computing ; Chapter 45. Review on reliability and energy-efficiency issues in cloud computing -- Section 11. Cognitive science. Chapter 46. Abductive s
505 0 $a Trust management mechanism in blockchain data science ; Chapter 107. Using machine learning to extract insights from consumer data -- Section 22. Ensemble learning. Chapter 108. Effective bankruptcy prediction models for North American companies ; Chapter 109. Ensemble methods and their applications ; Chapter 110. How to structure data for humanitarian learning ; Chapter 111. Stock price prediction: fuzzy clustering-based approach -- Section 23. Feature engineering. Chapter 112. A hybridized GA-based feature selection for text sentiment analysis -- Volume IV. Chapter 113. Bio-inspired algorithms for feature selection: a brief state of the art -- Section 24. Financial services analytics. Chapter 114. Financial analytics with big data ; Chapter 115. Portfolio optimization for the Indian stock market ; Chapter 116. Product offer and pricing personalization in retail banking -- Section 25. Fuzzy logic and soft computing. Chapter 117. Data hierarchies for generalization of imprecise data ; Chapter 118. Fuzzy complex system of linear equations ; Chapter 119. Fuzzy logic-based classification and authentication of beverages -- Section 26. Gradient-boosting decision trees. Chapter 120. Aircraft maintenance prediction tree algorithms -- Section 27. Graph learning. Chapter 121. Graph data management, modeling, and mining -- Section 28. High-throughput data analysis. Chapter 122. Best practices of feature selection in multi-omics data ; Chapter 123. Class discovery, comparison, and prediction methods for RNA-seq data -- Section 29. Industry 4.0. Chapter 124. AI is transforming insurance with five emerging business models ; Chapter 125. Artificial intelligence, big data, and machine learning in industry 4.0 ; Chapter 126. Big data and sustainability innovation ; Chapter 127. Deep learning for cyber security risk assessment in iiot systems ; Chapter 128. Digital transformation and circular economy for sustainability ; Chapter 129. Emerging new technologies and industrial revolution ; Chapter 130. Evolving from predictive to liquid maintenance in postmodern industry ; Chapter 131. Industrial revolution 4.0 with a focus on food-energy-water sectors ; Chapter 132. Industry revolution 4.0 and its impact on education ; Chapter 133. Sensors and data in mobile robotics for localisation ; Chapter 134. Structure implementation of online streams ; Chapter 135. Nature-inspired algorithms and smart city applications -- Section 30. Information extraction. Chapter 136. Analysis of frequency domain data generated by a quartz crystal -- Section 31. Internet of things. Chapter 137. Exploration of research challengesand potential applications in IoT ; Chapter 138. The application of the internet of things in managing supply chains -- Section 32. Malware analysis. Chapter 139. Malware detection in network flows with self-supervised deep learning -- Section 33. Management analytics. Chapter 140. Evaluation of tourism sustainability in La Habana city ; Chapter 141. The contribution of benefit management to improve organizational maturity -- Section 34. Marketing analytics. Chapter 142. Balanced scorecard as a tool to evaluate digital marketing activities -- Section 35. Mathematical optimization. Chapter 143. An approach for a multi-objective capacitated transportation problem ; Chapter 144. One vs.two vs. multidimensional searches for optimization methods -- Section 36. Meta-analysis and metamodeling. Chapter 145. The role of metamodeling in systems development -- Section 37. Multivariate analysis. Chapter 146. Challenges and chances of classical cox regression
520 3 $a "This book examines current, state-of-the-art research in the areas of data science, machine learning, data mining, optimization, artificial intelligence, statistics, and the interactions, linkages, and applications of knowledge-based business with information systems"-- $c Provided by publisher.
650 0 $a Big data. $3 609582
650 0 $a Data mining. $3 184440
650 0 $a Machine learning. $3 188639
655 4 $a Electronic books. $2 local. $3 214472
700 1 $a Wang, John, $d 1955-. $3 952630
710 2 $a IGI Global. $3 529832
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-9220-5