Preface. Acknowledgements. n1: Why Human-Centered e-Business? 1.1. Introduction. 1.2. e-Business and e-Commerce. 1.3. Converging Trends towards Human-Centeredness. 1.4. Technology-Centeredness vs Human-Centeredness. 1.5. Human-Centered Approach. 1.6. Organization Levels and e-Business. 1.7. Summary. References. n2: e-Business Concepts and Technologies. 2.1. Introduction. 2.2. e-Business Systems. 2.3. e-Business Strategies. 2.4. e-Business Models. 2.5. Internet and Web Technologies. 2.6. Intelligent Technologies. 2.7. Software Engineering Technologies. 2.8. Multimedia. 2.9. Summary. References. n3: Converging Trends towards Human-Centeredness and Enabling Theories. 3.1. Introduction. 3.2. Pragmatic Considerations for Human-Centered System Development. 3.3. Enabling Theories for Human-Centered Systems. 3.4. Discussion. 3.5. Summary. References. n4: Human-Centered e-Business System Development Framework. 4.1. Introduction. 4.2. Overview. 4.3. External and Internal Planes of Human-Centered Framework. 4.4. Components of the Human-Centered e-Business System Development Framework. 4.5. Activity-Centered e-Business Analysis Component. 4.6. Problem Solving Ontology Component. 4.7. Summary. References. n5: Human-Centered e-Business System Development Framework. 5.1. Introduction. 5.2. Problem Solving Ontology Component. 5.3. Human-Centered Criteria and Problem Solving Ontology.5.4. Transformation Agent Component. 5.5. Multimedia Interpretation Component. 5.6. Application of Multimedia Interpretation Component in Medical Diagnosis. 5.7. Emergent Characteristics of HCVM. 5.8. Summary. References. n6: e-Sales Recruitment. 6.1. Introduction. 6.2. Human Resources Management e-Business Systems. 6.3. Information Technology and Recruitment. 6.4. Activity-Centered e-Business Analysis of Sales Recruitment Activity. 6.5. Human-Centered Activity Model. 6.6.Implementation and Results. 6.7. Summary. References. n7: Customer Relationship Management and e-Banking. 7.1. Introduction. 7.2. Traditional Data Mining and Knowledge Discovery Process. 7.4. Data Mining and the Internet. 7.5. Multi-layered, Component-based Multi-Agent Distributed Data Mining Architecture. 7.6. Application in e-Banking. 7.7. Data Mining Implementation Results. 7.8. Summary. References. n8: HCVM Based Context-Dependent Data Organization for e-Commerce. 8.1. Introduction. 8.2. Context-Dependent Data Management. 8.3. Context-Modeling in XML. 8.4. Flexible Access to Context Information. 8.5. Sample Interaction. 8.6. Summary. References. n9: Human-Centered Knowledge Management. 9.1. Introduction. 9.2. HCVM Approach to Knowledge Sharing and Decision Support in Knowledge Management Systems. 9.3. Resource Description Format (RDF) for Knowledge Representation. 9.4. The Regional Innovation Leadership (RIL) Cycle. 9.5.
Human-Centered e-Business focuses on analysis, design and development of human-centered e-business systems. The authors illustrate the benefits of the human-centered approach in intelligent e-sales recruitment application, integrating data mining technology with decision support model for profiling transaction behavior of internet banking customers, user-centered context dependent data organization using XML, knowledge management, and optimizing the search process through human evaluation in an intelligent interactive multimedia application. The applications described in this work, facilitates both e-business analysis from a business professional's perspective, and human-centered system design from a system development perspective. These applications employ a range of internet and soft computing technologies.
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