Appications of data in EBusiness and Finance 1st Edition by Carlos Soares, Yonghong Peng, Jun Meng, Takashi Washio, Zhi Hua Zhou ISBN 1586038907 9781586038908

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Product details:
ISBN 10: 1586038907
ISBN 13: 9781586038908
Author: Carlos Soares, Yonghong Peng, Jun Meng, Takashi Washio, Zhi Hua Zhou

The application of Data Mining (DM) technologies has shown an explosive growth in an increasing number of different areas of business, government and science. Two of the most important business areas are finance, in particular in banks and insurance companies, and e-business, such as web portals, e-commerce and ad management services.In spite of the close relationship between research and practice in Data Mining, it is not easy to find information on some of the most important issues involved in real world application of DM technology, from business and data understanding to evaluation and deployment. Papers often describe research that was developed without taking into account constraints imposed by the motivating application. When these issues are taken into account, they are frequently not discussed in detail because the paper must focus on the method. Therefore knowledge that could be useful for those who would like to apply the same approach on a related problem is not shared. The papers in this book address some of these issues. This book is of interest not only to Data Mining researchers and practitioners, but also to students who wish to have an idea of the practical issues involved in Data Mining.

IOS Press is an international science, technical and medical publisher of high-quality books for academics, scientists, and professionals in all fields.

Appications of data in EBusiness and Finance 1st Edition Table of contents:

Part I: Foundations of Data Analytics in E-Business

2. E-Business Models and Data-Driven Decision Making

   • Overview of E-Business Models
   • The Role of Data in E-Business Strategy and Operations
   • Business Intelligence and Decision Support Systems
   • Data Mining Techniques for E-Business Optimization
   • Case Studies in Data-Driven E-Business Innovations

3. Data Collection and Management in E-Business

   • Sources of Data in E-Business: Transaction Data, Social Media, and More
   • Data Integration and Data Warehousing for E-Business
   • Data Quality, Cleaning, and Preprocessing Techniques
   • Real-Time Data Processing in E-Business Applications
   • Privacy, Ethics, and Data Governance in E-Business

4. Customer Relationship Management (CRM) and Data Analytics

   • CRM Systems and the Role of Data in Customer Retention
   • Predictive Analytics for Customer Behavior and Lifetime Value
   • Personalization and Targeted Marketing Strategies
   • Sentiment Analysis and Social Media Mining
   • Data-Driven Customer Segmentation and Profiling

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Part II: Data Applications in Finance

5. Introduction to Financial Data Analysis

   • Types of Financial Data and Their Applications
   • Quantitative Methods in Financial Data Analysis
   • Time-Series Analysis for Financial Market Predictions
   • Risk Management and Data-Driven Models
   • Regulatory and Ethical Considerations in Financial Data Usage

6. Credit Scoring and Risk Analysis

   • Models for Credit Scoring and Risk Assessment
   • Logistic Regression, Decision Trees, and Machine Learning in Credit Scoring
   • Predictive Analytics for Loan Default and Credit Risk
   • Case Studies in Financial Risk Management
   • Data Applications in Fraud Detection and Prevention

7. Algorithmic Trading and Financial Market Modeling

   • Introduction to Algorithmic Trading Systems
   • Machine Learning and Artificial Intelligence in Financial Trading
   • High-Frequency Trading and Data Processing Challenges
   • Quantitative Strategies and Data-Driven Predictions in Stock Markets
   • Risk Mitigation Techniques in Algorithmic Trading

8. Portfolio Management and Data Analytics

   • Data-Driven Portfolio Optimization Techniques
   • Modern Portfolio Theory and Advanced Risk Models
   • Use of Big Data in Asset Allocation and Diversification
   • Real-Time Data Analytics for Investment Decisions
   • Case Studies in Data-Driven Portfolio Management

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Part III: Cross-Domain Applications and Emerging Technologies

9. The Role of Big Data and Cloud Computing in E-Business and Finance

   • Big Data Technologies and Their Applications in Finance
   • Cloud-Based Solutions for Data Management and Analysis
   • Data Storage, Security, and Scalability in E-Business and Finance
   • The Future of Cloud Computing in Business and Financial Services
   • Case Studies of Cloud-Based Financial Services

10. Artificial Intelligence, Machine Learning, and Data-Driven Innovation

    • AI and ML Algorithms for Business and Financial Analytics
    • Predictive Modeling and Deep Learning in E-Business
    • Machine Learning for Fraud Detection and Risk Management
    • Natural Language Processing for Financial Text Analysis
    • Chatbots, Automation, and Data in Customer Services

11. Blockchain and Data Applications in E-Business and Finance

    • Introduction to Blockchain Technology and Its Impact on Business
    • Data Security, Transparency, and Privacy in Blockchain
    • Use Cases of Blockchain in E-Commerce and Financial Transactions
    • Decentralized Finance (DeFi) and Data-Driven Applications
    • The Future of Blockchain and Data in Business and Finance

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Part IV: Advanced Topics and Future Trends

12. Data Privacy, Security, and Ethics in E-Business and Finance

    • Challenges in Data Privacy and Security in Digital Transactions
    • Ethical Considerations in Financial Data Analytics
    • Regulatory Compliance in Financial Data Use (GDPR, etc.)
    • Data Anonymization and Secure Data Sharing
    • Balancing Innovation and Privacy Protection in Business

13. Predictive Analytics and Future Trends in E-Business and Finance

    • Predictive Analytics for Forecasting Business Trends and Financial Markets
    • The Role of Data in Shaping the Future of E-Commerce
    • Emerging Trends in AI, Blockchain, and Data Analytics
    • The Impact of Automation and Smart Contracts on Business Models
    • Future Challenges in Data-Driven E-Business and Finance

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