Encyclopedia of data science and machine learning:
"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"--
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :
IGI Global,
[2022]
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | "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"-- |
| Beschreibung: | 251 PDFs (5 volumes (3143 pages)) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781799892212 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
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| 245 | 0 | 0 | |a Encyclopedia of data science and machine learning |c John Wang, editor. |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : |b IGI Global, |c [2022] | |
| 300 | |a 251 PDFs (5 volumes (3143 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 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 challenges and 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 ; Chapter 147. Quantile regression applications in climate change -- Section 38. Natural language processing (NLP). Chapter 148. Challenges and opportunities in knowledge representation and reasoning -- Section 39. Nature-inspired algorithms. Chapter 149. Spatial audio coding and machine learning -- Volume V. Section 40. Network modeling and theory. Chapter 150. Binary search approach for largest cascade capacity of complex networks ; Chapter 151. Investigating the character-network topology in marvel movies ; Chapter 152. Social networks and analytics -- Section 41. Object detection. Chapter 153. An image-based ship detector with deep learning algorithms -- Section 42. Performance metrics. Chapter 154. Artificial intelligence and machine learning innovation in SDGs -- Section 43. Predictive analytics. Chapter 155. A comparison of SOM and K-means algorithms in predicting tax compliance ; Chapter 156. Analyzing the significance of learner emotions using data analytics ; Chapter 157. Breast cancer disease exploitation to recure a healthy lifestyle ; Chapter 158. Convex nonparametric least squares for predictive maintenance ; Chapter 159. Machine learning and sensor data fusion for emotion recognition ; Chapter 160. Predicting estimated arrival times in logistics using machine learning ; Chapter 161. Relative relations in biomedical data classification ; Chapter 162. Use of "odds" in Bayesian classifiers -- Section 44. Pricing analytics. Chapter 163. Machine learning for housing price prediction -- Section 45. Qualitative research. Chapter 164. Quantitative data in ethnography with Asian reflections -- Section 46. Recommender systems. Chapter 165. Content and context-aware recommender systems for business ; Chapter 166. ERP and time management: a recommender system ; Chapter 167. Foundational recommender systems for business ; Chapter 168. Hybrid machine learning for matchmaking in digital business ecosystems ; Chapter 169. Recommendation systems -- Section 47. Reinforcement learning. Chapter 170. Reinforcement learning for combinatorial optimization -- Section 48. Simulation and modeling. Chapter 171. A simulation model for application development in enterprise data platforms ; Chapter 172. Ontological metamodel of sustainable development -- Section 49. Smart city. Chapter 173. Death analytics and the potential role in smart cities -- Section 50. Social media analytics. Chapter 174. Usage of the basic facebook features as befitting marketing tools -- Section 51. Supply chain analytics and management. Chapter 175. A bio-inspired approach to solve the problem of regular carpooling ; Chapter 176. A review on the use of artificial intelligence in reverse logistics ; Chapter 177. Artificial intelligence for sustainable humanitarian logistics ; Chapter 178. Blockchain technology, vanilla production, and fighting global warming ; Chapter 179. Data analytics in the global product development supply chain ; Chapter 180. Digital twins, stress tests, and the need for resilient supply chains -- Section 52. Symbolic learning. Chapter 181. Knowledge-based artificial intelligence: methods and applications -- Section 53. Time series analysis. Chapter 182. Statistical model selection for seasonal big time series data -- Section 54. Transfer learning. Chapter 183. Integration of knowledge sharing into project management -- Section 55. Transport analytics. Chapter 184. Improving transportation planning using machine learning -- Section 56. Unsupervised and supervised learning. Chapter 185. Automaton: a gamification machine learning project ; Chapter 186. Employee classification in reward allocation using ML algorithms ; Chapter 187. Identifying disease and diagnosis in females using machine learning. | |
| 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 in manufacturing 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 for RDF 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 big data 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 software development -- 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 strategies in human cognition and in deep learning machines ; Chapter 47. Humanities, digitizing, and economics ; Chapter 48. The social impact of artificial intelligence -- Section 12. Computational intelligence. Chapter 49. AI-based emotion recognition ; Chapter 50. An intelligent virtual medical assistant for healthcare prediction ; Chapter 51. Artificial intelligence-based behavioral biometrics ; Chapter 52. Artificial neural networks and data science ; Chapter 53. Machine learning algorithms in human gait analysis ; Chapter 54. Machine learning algorithms: features and applications ; Chapter 55. Machine learning and emotions ; Chapter 56. Machine learning enables decision-making processes for an enterprise ; Chapter 57. Sentiment analysis using LSTM ; Chapter 58. Understanding machine learning concepts -- Section 13. Computational statistics. Chapter 59. Effect of large-scale performed vedic homa therapy on AQI ; Chapter 60. Imputation-based modeling for outcomes with ceiling and floor effect -- Section 14. Computer vision. Chapter 61. Validating machine vision competency against human vision -- Section 15. Customer analytics. Chapter 62. Customer analytics using sentiment analysis and net promoter score ; Chapter 63. Customer analytics: deep dive into customer data ; Chapter 64. Dynamics of user-generated content in industry 4.0 ; Chapter 65. Factors shaping the patterns of online shopping behavior ; Chapter 66. Semantic features revealed in consumer-review studies -- Section 16. Data processing, data pipeline, and data engineering. Chapter 67. Beyond technology: an integrative process model for data analytics ; Chapter 68. Bias in data-informed decision making ; Chapter 69. Data science in the database: using SQL for data preparation ; Chapter 70. Data science methodology ; Chapter 71. Machine learning experiment management with mlflow ; Chapter 72. Research data management -- Volume III. Chapter 73. Sustainable big data analytics process pipeline using apache ecosystem -- Section 17. Data visualization and visual mining. Chapter 74. An agent and pattern-oriented approach to data visualization ; Chapter 75. Big data visualization of association rules and frequent patterns ; Chapter 76. Cognitive biases and data visualization ; Chapter 77. Data mining for visualizing polluted gases -- Section 18. Decision, support system. Chapter 78. A systems analysis for air quality in urban ecology ; Chapter 79. Automatic moderation of user-generated content ; Chapter 80. Bayesian network-based decision support for pest management ; Chapter 81. Data-driven clinical decision support systems theory and research ; Chapter 82. Decision-making systems ; Chapter 83. Decision support systems and data science ; Chapter 84. Decision-making approaches for airport surrounding traffic management ; Chapter 85. From DSS to data science: the effect of industry 4.0 ; Chapter 86. Scrutinizing the analytic hierarchy process (AHP) ; Chapter 87. Software for teaching: case promethee ; Chapter 88. The diamond of innovation -- Section 19. Deep neural network (DNN) of deep learning. Chapter 89. Machine learning approach to art authentication ; Chapter 90. Machine learning for decision support in the ICU -- Section 20. E-learning technologies and tools. Chapter 91. Artificial intelligence in e-learning systems ; Chapter 92. Converging international cooperation supported by data structures ; Chapter 93. Online educational video recommendation system analysis ; Chapter 94. Tools and techniques of digital education -- Section 21. Emerging technologies, applications, and related issues. Chapter 95. Artificial intelligence into democratic decision making ; Chapter 96. Change management science innovation methodologies ; Chapter 97. Developing machine learning skills with no-code machine learning tools ; Chapter 98. Educational data mining and learning analytics in the 21st century ; Chapter 99. Emerging tools and technologies in data science ; Chapter 100. Explainable artificial intelligence ; Chapter 101. Fairness challenges in artificial intelligence ; Chapter 102. Integration of knowledge management in digital healthcare industries ; Chapter 103. Learning analytics for smart classrooms ; Chapter 104. Machine learning in the real world ; Chapter 105. The artificial intelligence in the sphere of the administrative law ; Chapter 106. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 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. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 02/11/2023). | ||
| 650 | 0 | |a Big data. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Machine learning. | |
| 700 | 1 | |a Wang, John |d 1955- |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
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| contents | 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 challenges and 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 ; Chapter 147. Quantile regression applications in climate change -- Section 38. Natural language processing (NLP). Chapter 148. Challenges and opportunities in knowledge representation and reasoning -- Section 39. Nature-inspired algorithms. Chapter 149. Spatial audio coding and machine learning -- Volume V. Section 40. Network modeling and theory. Chapter 150. Binary search approach for largest cascade capacity of complex networks ; Chapter 151. Investigating the character-network topology in marvel movies ; Chapter 152. Social networks and analytics -- Section 41. Object detection. Chapter 153. An image-based ship detector with deep learning algorithms -- Section 42. Performance metrics. Chapter 154. Artificial intelligence and machine learning innovation in SDGs -- Section 43. Predictive analytics. Chapter 155. A comparison of SOM and K-means algorithms in predicting tax compliance ; Chapter 156. Analyzing the significance of learner emotions using data analytics ; Chapter 157. Breast cancer disease exploitation to recure a healthy lifestyle ; Chapter 158. Convex nonparametric least squares for predictive maintenance ; Chapter 159. Machine learning and sensor data fusion for emotion recognition ; Chapter 160. Predicting estimated arrival times in logistics using machine learning ; Chapter 161. Relative relations in biomedical data classification ; Chapter 162. Use of "odds" in Bayesian classifiers -- Section 44. Pricing analytics. Chapter 163. Machine learning for housing price prediction -- Section 45. Qualitative research. Chapter 164. Quantitative data in ethnography with Asian reflections -- Section 46. Recommender systems. Chapter 165. Content and context-aware recommender systems for business ; Chapter 166. ERP and time management: a recommender system ; Chapter 167. Foundational recommender systems for business ; Chapter 168. Hybrid machine learning for matchmaking in digital business ecosystems ; Chapter 169. Recommendation systems -- Section 47. Reinforcement learning. Chapter 170. Reinforcement learning for combinatorial optimization -- Section 48. Simulation and modeling. Chapter 171. A simulation model for application development in enterprise data platforms ; Chapter 172. Ontological metamodel of sustainable development -- Section 49. Smart city. Chapter 173. Death analytics and the potential role in smart cities -- Section 50. Social media analytics. Chapter 174. Usage of the basic facebook features as befitting marketing tools -- Section 51. Supply chain analytics and management. Chapter 175. A bio-inspired approach to solve the problem of regular carpooling ; Chapter 176. A review on the use of artificial intelligence in reverse logistics ; Chapter 177. Artificial intelligence for sustainable humanitarian logistics ; Chapter 178. Blockchain technology, vanilla production, and fighting global warming ; Chapter 179. Data analytics in the global product development supply chain ; Chapter 180. Digital twins, stress tests, and the need for resilient supply chains -- Section 52. Symbolic learning. Chapter 181. Knowledge-based artificial intelligence: methods and applications -- Section 53. Time series analysis. Chapter 182. Statistical model selection for seasonal big time series data -- Section 54. Transfer learning. Chapter 183. Integration of knowledge sharing into project management -- Section 55. Transport analytics. Chapter 184. Improving transportation planning using machine learning -- Section 56. Unsupervised and supervised learning. Chapter 185. Automaton: a gamification machine learning project ; Chapter 186. Employee classification in reward allocation using ML algorithms ; Chapter 187. Identifying disease and diagnosis in females using machine learning. 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 in manufacturing 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 for RDF 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 big data 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 software development -- 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 strategies in human cognition and in deep learning machines ; Chapter 47. Humanities, digitizing, and economics ; Chapter 48. The social impact of artificial intelligence -- Section 12. Computational intelligence. Chapter 49. AI-based emotion recognition ; Chapter 50. An intelligent virtual medical assistant for healthcare prediction ; Chapter 51. Artificial intelligence-based behavioral biometrics ; Chapter 52. Artificial neural networks and data science ; Chapter 53. Machine learning algorithms in human gait analysis ; Chapter 54. Machine learning algorithms: features and applications ; Chapter 55. Machine learning and emotions ; Chapter 56. Machine learning enables decision-making processes for an enterprise ; Chapter 57. Sentiment analysis using LSTM ; Chapter 58. Understanding machine learning concepts -- Section 13. Computational statistics. Chapter 59. Effect of large-scale performed vedic homa therapy on AQI ; Chapter 60. Imputation-based modeling for outcomes with ceiling and floor effect -- Section 14. Computer vision. Chapter 61. Validating machine vision competency against human vision -- Section 15. Customer analytics. Chapter 62. Customer analytics using sentiment analysis and net promoter score ; Chapter 63. Customer analytics: deep dive into customer data ; Chapter 64. Dynamics of user-generated content in industry 4.0 ; Chapter 65. Factors shaping the patterns of online shopping behavior ; Chapter 66. Semantic features revealed in consumer-review studies -- Section 16. Data processing, data pipeline, and data engineering. Chapter 67. Beyond technology: an integrative process model for data analytics ; Chapter 68. Bias in data-informed decision making ; Chapter 69. Data science in the database: using SQL for data preparation ; Chapter 70. Data science methodology ; Chapter 71. Machine learning experiment management with mlflow ; Chapter 72. Research data management -- Volume III. Chapter 73. Sustainable big data analytics process pipeline using apache ecosystem -- Section 17. Data visualization and visual mining. Chapter 74. An agent and pattern-oriented approach to data visualization ; Chapter 75. Big data visualization of association rules and frequent patterns ; Chapter 76. Cognitive biases and data visualization ; Chapter 77. Data mining for visualizing polluted gases -- Section 18. Decision, support system. Chapter 78. A systems analysis for air quality in urban ecology ; Chapter 79. Automatic moderation of user-generated content ; Chapter 80. Bayesian network-based decision support for pest management ; Chapter 81. Data-driven clinical decision support systems theory and research ; Chapter 82. Decision-making systems ; Chapter 83. Decision support systems and data science ; Chapter 84. Decision-making approaches for airport surrounding traffic management ; Chapter 85. From DSS to data science: the effect of industry 4.0 ; Chapter 86. Scrutinizing the analytic hierarchy process (AHP) ; Chapter 87. Software for teaching: case promethee ; Chapter 88. The diamond of innovation -- Section 19. Deep neural network (DNN) of deep learning. Chapter 89. Machine learning approach to art authentication ; Chapter 90. Machine learning for decision support in the ICU -- Section 20. E-learning technologies and tools. Chapter 91. Artificial intelligence in e-learning systems ; Chapter 92. Converging international cooperation supported by data structures ; Chapter 93. Online educational video recommendation system analysis ; Chapter 94. Tools and techniques of digital education -- Section 21. Emerging technologies, applications, and related issues. Chapter 95. Artificial intelligence into democratic decision making ; Chapter 96. Change management science innovation methodologies ; Chapter 97. Developing machine learning skills with no-code machine learning tools ; Chapter 98. Educational data mining and learning analytics in the 21st century ; Chapter 99. Emerging tools and technologies in data science ; Chapter 100. Explainable artificial intelligence ; Chapter 101. Fairness challenges in artificial intelligence ; Chapter 102. Integration of knowledge management in digital healthcare industries ; Chapter 103. Learning analytics for smart classrooms ; Chapter 104. Machine learning in the real world ; Chapter 105. The artificial intelligence in the sphere of the administrative law ; Chapter 106. |
| ctrlnum | (CaBNVSL)slc00004015 (OCoLC)1369704434 |
| dewey-full | 005.7 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.7 |
| dewey-search | 005.7 |
| dewey-sort | 15.7 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :</subfield><subfield code="b">IGI Global,</subfield><subfield code="c">[2022]</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">251 PDFs (5 volumes (3143 pages))</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">electronic</subfield><subfield code="2">isbdmedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references and index.</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="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 challenges and 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 ; Chapter 147. Quantile regression applications in climate change -- Section 38. Natural language processing (NLP). Chapter 148. Challenges and opportunities in knowledge representation and reasoning -- Section 39. Nature-inspired algorithms. Chapter 149. Spatial audio coding and machine learning -- Volume V. Section 40. Network modeling and theory. Chapter 150. Binary search approach for largest cascade capacity of complex networks ; Chapter 151. Investigating the character-network topology in marvel movies ; Chapter 152. Social networks and analytics -- Section 41. Object detection. Chapter 153. An image-based ship detector with deep learning algorithms -- Section 42. Performance metrics. Chapter 154. Artificial intelligence and machine learning innovation in SDGs -- Section 43. Predictive analytics. Chapter 155. A comparison of SOM and K-means algorithms in predicting tax compliance ; Chapter 156. Analyzing the significance of learner emotions using data analytics ; Chapter 157. Breast cancer disease exploitation to recure a healthy lifestyle ; Chapter 158. Convex nonparametric least squares for predictive maintenance ; Chapter 159. Machine learning and sensor data fusion for emotion recognition ; Chapter 160. Predicting estimated arrival times in logistics using machine learning ; Chapter 161. Relative relations in biomedical data classification ; Chapter 162. Use of "odds" in Bayesian classifiers -- Section 44. Pricing analytics. Chapter 163. Machine learning for housing price prediction -- Section 45. Qualitative research. Chapter 164. Quantitative data in ethnography with Asian reflections -- Section 46. Recommender systems. Chapter 165. Content and context-aware recommender systems for business ; Chapter 166. ERP and time management: a recommender system ; Chapter 167. Foundational recommender systems for business ; Chapter 168. Hybrid machine learning for matchmaking in digital business ecosystems ; Chapter 169. Recommendation systems -- Section 47. Reinforcement learning. Chapter 170. Reinforcement learning for combinatorial optimization -- Section 48. Simulation and modeling. Chapter 171. A simulation model for application development in enterprise data platforms ; Chapter 172. Ontological metamodel of sustainable development -- Section 49. Smart city. Chapter 173. Death analytics and the potential role in smart cities -- Section 50. Social media analytics. Chapter 174. Usage of the basic facebook features as befitting marketing tools -- Section 51. Supply chain analytics and management. Chapter 175. A bio-inspired approach to solve the problem of regular carpooling ; Chapter 176. A review on the use of artificial intelligence in reverse logistics ; Chapter 177. Artificial intelligence for sustainable humanitarian logistics ; Chapter 178. Blockchain technology, vanilla production, and fighting global warming ; Chapter 179. Data analytics in the global product development supply chain ; Chapter 180. Digital twins, stress tests, and the need for resilient supply chains -- Section 52. Symbolic learning. Chapter 181. Knowledge-based artificial intelligence: methods and applications -- Section 53. Time series analysis. Chapter 182. Statistical model selection for seasonal big time series data -- Section 54. Transfer learning. Chapter 183. Integration of knowledge sharing into project management -- Section 55. Transport analytics. Chapter 184. Improving transportation planning using machine learning -- Section 56. Unsupervised and supervised learning. Chapter 185. Automaton: a gamification machine learning project ; Chapter 186. Employee classification in reward allocation using ML algorithms ; Chapter 187. Identifying disease and diagnosis in females using machine learning.</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="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 in manufacturing 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 for RDF 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 big data 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 software development -- 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 strategies in human cognition and in deep learning machines ; Chapter 47. Humanities, digitizing, and economics ; Chapter 48. The social impact of artificial intelligence -- Section 12. Computational intelligence. Chapter 49. AI-based emotion recognition ; Chapter 50. An intelligent virtual medical assistant for healthcare prediction ; Chapter 51. Artificial intelligence-based behavioral biometrics ; Chapter 52. Artificial neural networks and data science ; Chapter 53. Machine learning algorithms in human gait analysis ; Chapter 54. Machine learning algorithms: features and applications ; Chapter 55. Machine learning and emotions ; Chapter 56. Machine learning enables decision-making processes for an enterprise ; Chapter 57. Sentiment analysis using LSTM ; Chapter 58. Understanding machine learning concepts -- Section 13. Computational statistics. Chapter 59. Effect of large-scale performed vedic homa therapy on AQI ; Chapter 60. Imputation-based modeling for outcomes with ceiling and floor effect -- Section 14. Computer vision. Chapter 61. Validating machine vision competency against human vision -- Section 15. Customer analytics. Chapter 62. Customer analytics using sentiment analysis and net promoter score ; Chapter 63. Customer analytics: deep dive into customer data ; Chapter 64. Dynamics of user-generated content in industry 4.0 ; Chapter 65. Factors shaping the patterns of online shopping behavior ; Chapter 66. Semantic features revealed in consumer-review studies -- Section 16. Data processing, data pipeline, and data engineering. Chapter 67. Beyond technology: an integrative process model for data analytics ; Chapter 68. Bias in data-informed decision making ; Chapter 69. Data science in the database: using SQL for data preparation ; Chapter 70. Data science methodology ; Chapter 71. Machine learning experiment management with mlflow ; Chapter 72. Research data management -- Volume III. Chapter 73. Sustainable big data analytics process pipeline using apache ecosystem -- Section 17. Data visualization and visual mining. Chapter 74. An agent and pattern-oriented approach to data visualization ; Chapter 75. Big data visualization of association rules and frequent patterns ; Chapter 76. Cognitive biases and data visualization ; Chapter 77. Data mining for visualizing polluted gases -- Section 18. Decision, support system. Chapter 78. A systems analysis for air quality in urban ecology ; Chapter 79. Automatic moderation of user-generated content ; Chapter 80. Bayesian network-based decision support for pest management ; Chapter 81. Data-driven clinical decision support systems theory and research ; Chapter 82. Decision-making systems ; Chapter 83. Decision support systems and data science ; Chapter 84. Decision-making approaches for airport surrounding traffic management ; Chapter 85. From DSS to data science: the effect of industry 4.0 ; Chapter 86. Scrutinizing the analytic hierarchy process (AHP) ; Chapter 87. Software for teaching: case promethee ; Chapter 88. The diamond of innovation -- Section 19. Deep neural network (DNN) of deep learning. Chapter 89. Machine learning approach to art authentication ; Chapter 90. Machine learning for decision support in the ICU -- Section 20. E-learning technologies and tools. Chapter 91. Artificial intelligence in e-learning systems ; Chapter 92. Converging international cooperation supported by data structures ; Chapter 93. Online educational video recommendation system analysis ; Chapter 94. Tools and techniques of digital education -- Section 21. Emerging technologies, applications, and related issues. Chapter 95. Artificial intelligence into democratic decision making ; Chapter 96. Change management science innovation methodologies ; Chapter 97. Developing machine learning skills with no-code machine learning tools ; Chapter 98. Educational data mining and learning analytics in the 21st century ; Chapter 99. Emerging tools and technologies in data science ; Chapter 100. Explainable artificial intelligence ; Chapter 101. Fairness challenges in artificial intelligence ; Chapter 102. Integration of knowledge management in digital healthcare industries ; Chapter 103. Learning analytics for smart classrooms ; Chapter 104. Machine learning in the real world ; Chapter 105. The artificial intelligence in the sphere of the administrative law ; Chapter 106. </subfield></datafield><datafield tag="506" ind1=" " ind2=" "><subfield code="a">Restricted to subscribers or individual electronic text purchasers.</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="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"--</subfield><subfield code="c">Provided by publisher.</subfield></datafield><datafield tag="530" ind1=" " ind2=" "><subfield code="a">Also available in print.</subfield></datafield><datafield tag="538" ind1=" " ind2=" "><subfield code="a">Mode of access: World Wide Web.</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on title screen (IGI Global, viewed 02/11/2023).</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Big data.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Data mining.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Machine learning.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, John</subfield><subfield code="d">1955-</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="710" ind1="2" ind2=" "><subfield code="a">IGI Global,</subfield><subfield code="e">publisher.</subfield></datafield><datafield tag="776" ind1="0" ind2=" "><subfield code="c">(Original)</subfield><subfield code="w">(DLC)2021027690</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Print version:</subfield><subfield code="z">1799892204</subfield><subfield code="z">9781799892205</subfield><subfield code="w">(DLC) 2021027690</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="l">FWS01</subfield><subfield code="p">ZDB-98-IGB</subfield><subfield code="q">FWS_PDA_IGB</subfield><subfield code="u">http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-9220-5</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-98-IGB</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-863</subfield></datafield></record></collection> |
| id | ZDB-98-IGB-00276507 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-26T14:51:58Z |
| institution | BVB |
| isbn | 9781799892212 |
| language | English |
| oclc_num | 1369704434 |
| open_access_boolean | |
| owner | DE-863 DE-BY-FWS |
| owner_facet | DE-863 DE-BY-FWS |
| physical | 251 PDFs (5 volumes (3143 pages)) Also available in print. |
| psigel | ZDB-98-IGB |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | IGI Global, |
| record_format | marc |
| spelling | Encyclopedia of data science and machine learning John Wang, editor. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, [2022] 251 PDFs (5 volumes (3143 pages)) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. 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 challenges and 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 ; Chapter 147. Quantile regression applications in climate change -- Section 38. Natural language processing (NLP). Chapter 148. Challenges and opportunities in knowledge representation and reasoning -- Section 39. Nature-inspired algorithms. Chapter 149. Spatial audio coding and machine learning -- Volume V. Section 40. Network modeling and theory. Chapter 150. Binary search approach for largest cascade capacity of complex networks ; Chapter 151. Investigating the character-network topology in marvel movies ; Chapter 152. Social networks and analytics -- Section 41. Object detection. Chapter 153. An image-based ship detector with deep learning algorithms -- Section 42. Performance metrics. Chapter 154. Artificial intelligence and machine learning innovation in SDGs -- Section 43. Predictive analytics. Chapter 155. A comparison of SOM and K-means algorithms in predicting tax compliance ; Chapter 156. Analyzing the significance of learner emotions using data analytics ; Chapter 157. Breast cancer disease exploitation to recure a healthy lifestyle ; Chapter 158. Convex nonparametric least squares for predictive maintenance ; Chapter 159. Machine learning and sensor data fusion for emotion recognition ; Chapter 160. Predicting estimated arrival times in logistics using machine learning ; Chapter 161. Relative relations in biomedical data classification ; Chapter 162. Use of "odds" in Bayesian classifiers -- Section 44. Pricing analytics. Chapter 163. Machine learning for housing price prediction -- Section 45. Qualitative research. Chapter 164. Quantitative data in ethnography with Asian reflections -- Section 46. Recommender systems. Chapter 165. Content and context-aware recommender systems for business ; Chapter 166. ERP and time management: a recommender system ; Chapter 167. Foundational recommender systems for business ; Chapter 168. Hybrid machine learning for matchmaking in digital business ecosystems ; Chapter 169. Recommendation systems -- Section 47. Reinforcement learning. Chapter 170. Reinforcement learning for combinatorial optimization -- Section 48. Simulation and modeling. Chapter 171. A simulation model for application development in enterprise data platforms ; Chapter 172. Ontological metamodel of sustainable development -- Section 49. Smart city. Chapter 173. Death analytics and the potential role in smart cities -- Section 50. Social media analytics. Chapter 174. Usage of the basic facebook features as befitting marketing tools -- Section 51. Supply chain analytics and management. Chapter 175. A bio-inspired approach to solve the problem of regular carpooling ; Chapter 176. A review on the use of artificial intelligence in reverse logistics ; Chapter 177. Artificial intelligence for sustainable humanitarian logistics ; Chapter 178. Blockchain technology, vanilla production, and fighting global warming ; Chapter 179. Data analytics in the global product development supply chain ; Chapter 180. Digital twins, stress tests, and the need for resilient supply chains -- Section 52. Symbolic learning. Chapter 181. Knowledge-based artificial intelligence: methods and applications -- Section 53. Time series analysis. Chapter 182. Statistical model selection for seasonal big time series data -- Section 54. Transfer learning. Chapter 183. Integration of knowledge sharing into project management -- Section 55. Transport analytics. Chapter 184. Improving transportation planning using machine learning -- Section 56. Unsupervised and supervised learning. Chapter 185. Automaton: a gamification machine learning project ; Chapter 186. Employee classification in reward allocation using ML algorithms ; Chapter 187. Identifying disease and diagnosis in females using machine learning. 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 in manufacturing 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 for RDF 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 big data 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 software development -- 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 strategies in human cognition and in deep learning machines ; Chapter 47. Humanities, digitizing, and economics ; Chapter 48. The social impact of artificial intelligence -- Section 12. Computational intelligence. Chapter 49. AI-based emotion recognition ; Chapter 50. An intelligent virtual medical assistant for healthcare prediction ; Chapter 51. Artificial intelligence-based behavioral biometrics ; Chapter 52. Artificial neural networks and data science ; Chapter 53. Machine learning algorithms in human gait analysis ; Chapter 54. Machine learning algorithms: features and applications ; Chapter 55. Machine learning and emotions ; Chapter 56. Machine learning enables decision-making processes for an enterprise ; Chapter 57. Sentiment analysis using LSTM ; Chapter 58. Understanding machine learning concepts -- Section 13. Computational statistics. Chapter 59. Effect of large-scale performed vedic homa therapy on AQI ; Chapter 60. Imputation-based modeling for outcomes with ceiling and floor effect -- Section 14. Computer vision. Chapter 61. Validating machine vision competency against human vision -- Section 15. Customer analytics. Chapter 62. Customer analytics using sentiment analysis and net promoter score ; Chapter 63. Customer analytics: deep dive into customer data ; Chapter 64. Dynamics of user-generated content in industry 4.0 ; Chapter 65. Factors shaping the patterns of online shopping behavior ; Chapter 66. Semantic features revealed in consumer-review studies -- Section 16. Data processing, data pipeline, and data engineering. Chapter 67. Beyond technology: an integrative process model for data analytics ; Chapter 68. Bias in data-informed decision making ; Chapter 69. Data science in the database: using SQL for data preparation ; Chapter 70. Data science methodology ; Chapter 71. Machine learning experiment management with mlflow ; Chapter 72. Research data management -- Volume III. Chapter 73. Sustainable big data analytics process pipeline using apache ecosystem -- Section 17. Data visualization and visual mining. Chapter 74. An agent and pattern-oriented approach to data visualization ; Chapter 75. Big data visualization of association rules and frequent patterns ; Chapter 76. Cognitive biases and data visualization ; Chapter 77. Data mining for visualizing polluted gases -- Section 18. Decision, support system. Chapter 78. A systems analysis for air quality in urban ecology ; Chapter 79. Automatic moderation of user-generated content ; Chapter 80. Bayesian network-based decision support for pest management ; Chapter 81. Data-driven clinical decision support systems theory and research ; Chapter 82. Decision-making systems ; Chapter 83. Decision support systems and data science ; Chapter 84. Decision-making approaches for airport surrounding traffic management ; Chapter 85. From DSS to data science: the effect of industry 4.0 ; Chapter 86. Scrutinizing the analytic hierarchy process (AHP) ; Chapter 87. Software for teaching: case promethee ; Chapter 88. The diamond of innovation -- Section 19. Deep neural network (DNN) of deep learning. Chapter 89. Machine learning approach to art authentication ; Chapter 90. Machine learning for decision support in the ICU -- Section 20. E-learning technologies and tools. Chapter 91. Artificial intelligence in e-learning systems ; Chapter 92. Converging international cooperation supported by data structures ; Chapter 93. Online educational video recommendation system analysis ; Chapter 94. Tools and techniques of digital education -- Section 21. Emerging technologies, applications, and related issues. Chapter 95. Artificial intelligence into democratic decision making ; Chapter 96. Change management science innovation methodologies ; Chapter 97. Developing machine learning skills with no-code machine learning tools ; Chapter 98. Educational data mining and learning analytics in the 21st century ; Chapter 99. Emerging tools and technologies in data science ; Chapter 100. Explainable artificial intelligence ; Chapter 101. Fairness challenges in artificial intelligence ; Chapter 102. Integration of knowledge management in digital healthcare industries ; Chapter 103. Learning analytics for smart classrooms ; Chapter 104. Machine learning in the real world ; Chapter 105. The artificial intelligence in the sphere of the administrative law ; Chapter 106. Restricted to subscribers or individual electronic text purchasers. "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"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 02/11/2023). Big data. Data mining. Machine learning. Wang, John 1955- editor. IGI Global, publisher. (Original) (DLC)2021027690 Print version: 1799892204 9781799892205 (DLC) 2021027690 FWS01 ZDB-98-IGB FWS_PDA_IGB http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-9220-5 Volltext |
| spellingShingle | Encyclopedia of data science and machine learning 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 challenges and 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 ; Chapter 147. Quantile regression applications in climate change -- Section 38. Natural language processing (NLP). Chapter 148. Challenges and opportunities in knowledge representation and reasoning -- Section 39. Nature-inspired algorithms. Chapter 149. Spatial audio coding and machine learning -- Volume V. Section 40. Network modeling and theory. Chapter 150. Binary search approach for largest cascade capacity of complex networks ; Chapter 151. Investigating the character-network topology in marvel movies ; Chapter 152. Social networks and analytics -- Section 41. Object detection. Chapter 153. An image-based ship detector with deep learning algorithms -- Section 42. Performance metrics. Chapter 154. Artificial intelligence and machine learning innovation in SDGs -- Section 43. Predictive analytics. Chapter 155. A comparison of SOM and K-means algorithms in predicting tax compliance ; Chapter 156. Analyzing the significance of learner emotions using data analytics ; Chapter 157. Breast cancer disease exploitation to recure a healthy lifestyle ; Chapter 158. Convex nonparametric least squares for predictive maintenance ; Chapter 159. Machine learning and sensor data fusion for emotion recognition ; Chapter 160. Predicting estimated arrival times in logistics using machine learning ; Chapter 161. Relative relations in biomedical data classification ; Chapter 162. Use of "odds" in Bayesian classifiers -- Section 44. Pricing analytics. Chapter 163. Machine learning for housing price prediction -- Section 45. Qualitative research. Chapter 164. Quantitative data in ethnography with Asian reflections -- Section 46. Recommender systems. Chapter 165. Content and context-aware recommender systems for business ; Chapter 166. ERP and time management: a recommender system ; Chapter 167. Foundational recommender systems for business ; Chapter 168. Hybrid machine learning for matchmaking in digital business ecosystems ; Chapter 169. Recommendation systems -- Section 47. Reinforcement learning. Chapter 170. Reinforcement learning for combinatorial optimization -- Section 48. Simulation and modeling. Chapter 171. A simulation model for application development in enterprise data platforms ; Chapter 172. Ontological metamodel of sustainable development -- Section 49. Smart city. Chapter 173. Death analytics and the potential role in smart cities -- Section 50. Social media analytics. Chapter 174. Usage of the basic facebook features as befitting marketing tools -- Section 51. Supply chain analytics and management. Chapter 175. A bio-inspired approach to solve the problem of regular carpooling ; Chapter 176. A review on the use of artificial intelligence in reverse logistics ; Chapter 177. Artificial intelligence for sustainable humanitarian logistics ; Chapter 178. Blockchain technology, vanilla production, and fighting global warming ; Chapter 179. Data analytics in the global product development supply chain ; Chapter 180. Digital twins, stress tests, and the need for resilient supply chains -- Section 52. Symbolic learning. Chapter 181. Knowledge-based artificial intelligence: methods and applications -- Section 53. Time series analysis. Chapter 182. Statistical model selection for seasonal big time series data -- Section 54. Transfer learning. Chapter 183. Integration of knowledge sharing into project management -- Section 55. Transport analytics. Chapter 184. Improving transportation planning using machine learning -- Section 56. Unsupervised and supervised learning. Chapter 185. Automaton: a gamification machine learning project ; Chapter 186. Employee classification in reward allocation using ML algorithms ; Chapter 187. Identifying disease and diagnosis in females using machine learning. 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 in manufacturing 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 for RDF 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 big data 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 software development -- 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 strategies in human cognition and in deep learning machines ; Chapter 47. Humanities, digitizing, and economics ; Chapter 48. The social impact of artificial intelligence -- Section 12. Computational intelligence. Chapter 49. AI-based emotion recognition ; Chapter 50. An intelligent virtual medical assistant for healthcare prediction ; Chapter 51. Artificial intelligence-based behavioral biometrics ; Chapter 52. Artificial neural networks and data science ; Chapter 53. Machine learning algorithms in human gait analysis ; Chapter 54. Machine learning algorithms: features and applications ; Chapter 55. Machine learning and emotions ; Chapter 56. Machine learning enables decision-making processes for an enterprise ; Chapter 57. Sentiment analysis using LSTM ; Chapter 58. Understanding machine learning concepts -- Section 13. Computational statistics. Chapter 59. Effect of large-scale performed vedic homa therapy on AQI ; Chapter 60. Imputation-based modeling for outcomes with ceiling and floor effect -- Section 14. Computer vision. Chapter 61. Validating machine vision competency against human vision -- Section 15. Customer analytics. Chapter 62. Customer analytics using sentiment analysis and net promoter score ; Chapter 63. Customer analytics: deep dive into customer data ; Chapter 64. Dynamics of user-generated content in industry 4.0 ; Chapter 65. Factors shaping the patterns of online shopping behavior ; Chapter 66. Semantic features revealed in consumer-review studies -- Section 16. Data processing, data pipeline, and data engineering. Chapter 67. Beyond technology: an integrative process model for data analytics ; Chapter 68. Bias in data-informed decision making ; Chapter 69. Data science in the database: using SQL for data preparation ; Chapter 70. Data science methodology ; Chapter 71. Machine learning experiment management with mlflow ; Chapter 72. Research data management -- Volume III. Chapter 73. Sustainable big data analytics process pipeline using apache ecosystem -- Section 17. Data visualization and visual mining. Chapter 74. An agent and pattern-oriented approach to data visualization ; Chapter 75. Big data visualization of association rules and frequent patterns ; Chapter 76. Cognitive biases and data visualization ; Chapter 77. Data mining for visualizing polluted gases -- Section 18. Decision, support system. Chapter 78. A systems analysis for air quality in urban ecology ; Chapter 79. Automatic moderation of user-generated content ; Chapter 80. Bayesian network-based decision support for pest management ; Chapter 81. Data-driven clinical decision support systems theory and research ; Chapter 82. Decision-making systems ; Chapter 83. Decision support systems and data science ; Chapter 84. Decision-making approaches for airport surrounding traffic management ; Chapter 85. From DSS to data science: the effect of industry 4.0 ; Chapter 86. Scrutinizing the analytic hierarchy process (AHP) ; Chapter 87. Software for teaching: case promethee ; Chapter 88. The diamond of innovation -- Section 19. Deep neural network (DNN) of deep learning. Chapter 89. Machine learning approach to art authentication ; Chapter 90. Machine learning for decision support in the ICU -- Section 20. E-learning technologies and tools. Chapter 91. Artificial intelligence in e-learning systems ; Chapter 92. Converging international cooperation supported by data structures ; Chapter 93. Online educational video recommendation system analysis ; Chapter 94. Tools and techniques of digital education -- Section 21. Emerging technologies, applications, and related issues. Chapter 95. Artificial intelligence into democratic decision making ; Chapter 96. Change management science innovation methodologies ; Chapter 97. Developing machine learning skills with no-code machine learning tools ; Chapter 98. Educational data mining and learning analytics in the 21st century ; Chapter 99. Emerging tools and technologies in data science ; Chapter 100. Explainable artificial intelligence ; Chapter 101. Fairness challenges in artificial intelligence ; Chapter 102. Integration of knowledge management in digital healthcare industries ; Chapter 103. Learning analytics for smart classrooms ; Chapter 104. Machine learning in the real world ; Chapter 105. The artificial intelligence in the sphere of the administrative law ; Chapter 106. Big data. Data mining. Machine learning. |
| title | Encyclopedia of data science and machine learning |
| title_auth | Encyclopedia of data science and machine learning |
| title_exact_search | Encyclopedia of data science and machine learning |
| title_full | Encyclopedia of data science and machine learning John Wang, editor. |
| title_fullStr | Encyclopedia of data science and machine learning John Wang, editor. |
| title_full_unstemmed | Encyclopedia of data science and machine learning John Wang, editor. |
| title_short | Encyclopedia of data science and machine learning |
| title_sort | encyclopedia of data science and machine learning |
| topic | Big data. Data mining. Machine learning. |
| topic_facet | Big data. Data mining. Machine learning. |
| url | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-9220-5 |
| work_keys_str_mv | AT wangjohn encyclopediaofdatascienceandmachinelearning AT igiglobal encyclopediaofdatascienceandmachinelearning |