دانلود کتاب Applied Artificial Intelligence in Business: Concepts and Cases

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Preface
Contents
Part I: Artificial Intelligence Concepts
1: Artificial Intelligence for Business
1.1 Introduction
1.2 AI Origin and Commercialization
1.3 Big Data Fueling Artificial Intelligence
1.4 Technology Landscape of AI in Business
1.5 Business Perspectives on Artificial Intelligence
References
2: Big Data Powering Business Intelligence
2.1 Introduction
2.2 Business Process and Big Data
2.2.1 Data from Business Operations
2.2.2 Social Media Data
2.2.3 Types of Business Data
2.2.4 Big Data in Business
2.3 Big Data Analytics
2.4 Business Analytics
2.5 Business Intelligence
2.5.1 Data Mining
2.5.2 Data Warehousing
2.6 Cloud Technology and Big Data Analytics
References
3: Artificial Intelligence Technologies for Business Applications
3.1 Introduction
3.2 Expert Systems
3.3 Robotic Process Automation
3.4 Fuzzy Logic
3.5 Interactive Decision Support Systems
3.6 Time Series Forecasting
3.7 Case-Based Reasoning
3.8 Procedural Content Generation
3.9 Voice Chatbots
3.10 Genetic Algorithm-Radial Basis Function (GA-RBF)
3.11 Hybrid AI Systems
References
4: Machine Learning for Business Applications
4.1 Introduction
4.2 Three Types of Machine Learning
4.2.1 Supervised Learning
4.2.2 Unsupervised Learning
4.2.3 Reinforcement Learning
4.3 Machine Learning Algorithms
4.3.1 Linear and Multiple Regression
4.3.2 Polynomial and Logistic Regression
4.3.3 Decision Tree
4.3.4 Neural Networks
4.3.5 Deep Learning
4.3.5.1 Convolutional Neural Networks
4.3.5.2 Recurrent Neural Network
4.3.6 Genetic Algorithms
4.3.7 Support Vector Machine
4.3.8 Naive Bayes Algorithm
4.3.9 Bayesian Network
References
Part II: Artificial Intelligence for Core Business Functions
5: Artificial Intelligence in Marketing and Sales
5.1 Introduction
5.2 The Development of AI Technologies in Marketing
5.3 AI Technologies for Marketing
5.3.1 Deep Learning
5.3.2 Artificial Neural Networks (ANNs)
5.3.3 Naïve Bayes Classifier
5.3.4 Decision Tree
5.3.5 Anomaly Detection
5.3.6 Genetic Algorithms
5.3.7 Rule-Based System
5.4 Application Areas of AI in Marketing
5.4.1 Market Segmentation and Targeting
5.4.2 Sales and Product Pricing
5.4.3 Market Research and Forecasting
5.4.4 Advertising
5.4.5 Brand Positioning
5.5 Key Takeaways
5.6 Conclusion
References
6: Artificial Intelligence for Customer Service
6.1 Introduction
6.2 The Development of AI in Customer Service
6.3 AI Technologies for Customer Service
6.3.1 Deep Learning
6.3.2 Support Vector Machines
6.3.3 Naive Bayesian Classification
6.3.4 Natural Language Processing
6.3.5 Hybrid AI Systems
6.4 Features of AI Applications in Customer Service
6.4.1 Collaborative Filtering
6.4.2 Customer Churn Analysis
6.4.3 Social Media Analytics
6.4.4 Customer Loyalty Programs
6.5 Key Takeaways
6.6 Conclusion
References
7: Artificial Intelligence in Finance
7.1 Introduction
7.2 Development of AI in Finance
7.3 AI Technologies in Finance and Banking
7.3.1 Financial Expert Systems
7.3.2 Machine Learning
7.3.3 Artificial Neural Network in Finance
7.3.4 Decision Analytics Network
7.3.5 AI Robo-Advisors
7.4 Features of AI Applications in Financial Services
7.4.1 Investment Banking
7.4.2 Personalized Finance
7.4.3 Credit Management
7.4.4 Loans and Lending
7.4.5 Asset Management
7.4.6 High-Frequency Trading
7.4.7 Fraud Detection and Security
7.4.8 The “FinTech and RegTech” Paradigm
7.5 Key Takeaways
7.6 Conclusions
References
8: Artificial Intelligence in Accounting and Auditing
8.1 Introduction
8.2 Development of AI in Accounting
8.3 Enabling Technologies for AI in Accounting
8.4 Features of AI Applications in Accounting
8.4.1 General Accounting
8.4.2 Accounts Payable
8.4.3 Purchasing
8.4.4 Accounts Receivable
8.4.5 Payment Processing
8.4.6 Billing and Invoicing
8.4.7 Debt Collection
8.4.8 Financial Reporting
8.4.9 Auditing
8.4.10 Financial Fraud Detection
8.4.11 Financial Risk Management
8.5 Key Takeaways
8.6 Conclusion
References
9: Artificial Intelligence in Human Resources
9.1 Introduction
9.2 Development of AI in HRM
9.3 AI Technologies in HR
9.4 AI Applications for HR Functions
9.4.1 Employee Recruitment
9.4.2 Employee Scheduling Management
9.4.3 Employee Training Management
9.4.4 Employee Turnover and Retention
9.4.5 Performance and Engagement Management
9.5 Key Takeaways
9.6 Conclusion
References
10: AI in Supply Chain and Logistics
10.1 Introduction
10.2 Development of AI Technology in Supply Chain
10.3 Enabling Artificial Intelligence Technologies for SCM
10.4 Application Areas of AI in SCM
10.5 Conclusion
References
11: Artificial Intelligence in Manufacturing
11.1 Introduction
11.2 Development of Artificial Intelligence in Manufacturing
11.3 Application Areas of AI in Manufacturing
11.4 AI Technologies in Manufacturing
11.4.1 Semantic Web of Things for Industry 4.0 (SWEeTI) Platform
11.4.2 Interoperative STEP-NC Computer-Aided Manufacturing and Intelligent Agent Systems
11.4.3 Fuzzy Interference, Relational Databases, and Rule-Based Decision-Making Systems
11.4.4 Time-Series Forecasting and Recurrent Neural Networks
11.4.5 Other AI Technologies and Applications
11.5 Key Takeaways
11.6 Conclusion
References
Part III: Artificial Intelligence for Industrial Applications
12: Artificial Intelligence in Insurance
12.1 Introduction
12.2 The Development of Insurance Technology
12.3 Enabling Technologies of AI for Insurtech
12.3.1 Chatbot and Natural Language Processing
12.3.2 Robotic Process Automation
12.3.3 Computer Vision
12.3.4 Telematics
12.3.5 Predictive Analytics
12.4 AI Applications in the Insurance Industry
12.4.1 Claims Process
12.4.2 Fraud Detection
12.4.3 Personalized Policies
12.5 Key Takeaways
12.6 Conclusion
References
13: Artificial Intelligence in Credit, Lending, and Mortgage
13.1 Introduction
13.2 Technology Development
13.3 AI Applications in Various Areas
13.4 Key Takeaways
13.5 Conclusion
References
14: Artificial Intelligence in Tourism and Hospitality
14.1 Introduction
14.2 Development of AI in Tourism
14.3 Enabling Technology for AI in Tourism
14.3.1 Expert System
14.3.2 Chatbots
14.3.3 Artificial Neural Network
14.3.4 Belief Network
14.3.5 Sentiment Analysis
14.3.6 Fuzzy Logic Systems
14.3.7 Virtual Reality
14.4 Applications of AI in Tourism
14.4.1 Smart Tourism
14.4.2 Demand Forecasting
14.4.3 Customer Data Analytics
14.5 Conclusion
References
15: Artificial Intelligence in Transportation
15.1 Introduction
15.2 Development of Autonomous Vehicles
15.3 AI Technology in Autonomous Vehicles
15.4 Applications of AI in the Transportation Industry
15.5 Future Trends
15.6 Conclusion
References
16: Artificial Intelligence in Real Estate
16.1 Introduction
16.2 AI Technologies for Real Estate
16.3 AI-Supported Real Estate Platforms
16.3.1 Houzen Real Estate Platform
16.3.2 Finding a Home Through NeighborhoodScout
16.3.3 Homesnap App
16.4 Conclusion
References
17: Artificial Intelligence in Education
17.1 Introduction
17.2 Evolution of AI in Education
17.3 Applications of AI in Learning Platforms
17.4 Features of AI in Education
17.4.1 Learning Personalization
17.4.2 Teaching Customization
17.4.3 Effectiveness
17.4.4 Smart Contents
17.4.5 Big Data Driven
17.5 Key Takeaways
17.5.1 Impacts on Learning Style
17.5.2 Impacts on Teachers
17.5.3 Impact on Business
17.6 Conclusion
References
18: Artificial Intelligence in Healthcare
18.1 Introduction
18.2 Evolution of AI in Healthcare
18.3 Current AI Technologies in Healthcare
18.4 Major Categories of AI in Healthcare
18.5 Key Takeaways
18.6 Conclusion
References
19: Artificial Intelligence in Energy
19.1 Introduction
19.2 Evolution of AI in Energy
19.3 Features of AI Applications in Energy
19.3.1 Smart Grid
19.3.2 Smart Homes
19.3.3 Renewable and Nonrenewable Resources
19.4 Conclusion
References
20: AI in Media and Entertainment
20.1 Introduction
20.2 AI for Traditional Media Services
20.2.1 AI for Television Broadcasting
20.2.2 AI for Radiobroadcasting
20.2.3 AI in Journalism and Print Media
20.2.4 AI in Cinema and Films
20.3 AI for New Media Streaming Services
20.4 AI for Social Media and Web Analytics
20.5 AI for Music Industry
20.5.1 Music Research
20.5.2 Music Psychology
20.6 Key Takeaways and Outlook
20.7 Conclusion
References
21: Artificial Intelligence in Fashion
21.1 Introduction
21.2 Current AI Applications
21.3 AI Applications for Fashion
21.4 Conclusion
References
22: Artificial Intelligence in Video Games and eSports
22.1 Introduction
22.2 Evolution of AI in Video Games and eSports
22.3 Enabling Technologies for AI in Gaming
22.3.1 Big Data in Gaming
22.3.2 Virtual Reality and AI in Gaming
22.3.3 Graphics Processing Units and AI Chips
22.3.4 Online Gaming and Cloud Platforms
22.4 AI Applications in Video Games and eSports
22.4.1 AI Opponents
22.4.2 AI Hirelings, Followers, and Non-Player Characters
22.4.3 Procedural Content Generation
22.4.4 Player Experience Modeling
22.4.5 Antisocial Behavior Detection and Governance in Multiplayer Gaming
22.4.6 Win Prediction
22.4.7 Intelligent Tutoring and Training
22.4.8 Player Telemetry Sign-Up, Engagement, and Retention Analytics
22.5 Key Takeaways
22.6 Conclusion
References
23: Artificial Intelligence in Sports
23.1 Introduction
23.2 AI for Sports Management
23.3 AI Applications for Basketball
23.4 AI Applications for Baseball
23.5 AI Applications for Golf
23.6 Conclusion
References
Index