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Advancing Information Management through Semantic Web Concepts and Ontologies

Book Description

Although the majority of information that is published by the current web is aimed at human consumption, the browsers which contain this information are only able to interpret HTML mark-up to visualize this content. Semantic web intends to address the stability between human and machine.Advancing Information Management through Semantic Web Concepts and Ontologies provides an analysis and introduction on the concept of combining the areas of semantic web and web mining. Emphasizing semantics in technologies, reasoning, content searching and social media, this book aims to be an essential source for practitioners, researchers and academics alike.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. EDITORIAL ADVISORY BOARD
  5. Preface
    1. INTRODUCTION
    2. OBJECTIVE OF THE BOOK
    3. CONTENTS OF THE BOOK
  6. Acknowledgment
  7. Chapter 1: Understanding Children’s Private Speech and Self-Regulation Learning in Web 2.0
    1. ABSTRACT
    2. INTRODUCTION
    3. PRIVATE SPEECH (PS)
    4. CURRENT DEFINITIONS AND MODELS
    5. SELF-REGULATION LEARNING (SRL)
    6. AGINIAN’S STUDIES: AN OVERVIEW
    7. CRITIQUES ON CHILDREN’S SPEECH AND SELF-REGULATION
    8. CONCLUSION AND REFLECTION
  8. Chapter 2: Emergent Ontologies by Collaborative Tagging for Knowledge Management
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PROPOSAL
    5. PROTOTYPE: AUTOMATIC COLLABORATIVE TAGGING (ACOTA)
    6. METHODOLOGY
  9. Chapter 3: Visualizing Design Project Knowledge on a Collaborative Web 2.0 Platform
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORK
    4. PROTOTYPE ARCHITECTURE AND IMPLEMENTATION
    5. PRODUCT AND PROCESS KNOWLEDGE VISUALIZATION
    6. VALIDATION SETUP AND RESULTS
    7. CONCLUSION
  10. Chapter 4: Multimedia Systems Development
    1. ABSTRACT
    2. INTRODUCTION
    3. TRADITIONAL VS. MULTIMEDIA INFORMATION SYSTEMS
    4. STATE OF THE ART
    5. EXISTING DEVELOPMENT METHODOLOGIES FOR MULTIMEDIA INFORMATION SYSTEMS
    6. MULTIMEDIA METADATA
    7. METHODOLOGIES FOR DEVELOPING MULTIMEDIA CONTENT
    8. DETECTED ISSUES AND POSSIBLE SOLUTIONS
    9. CONCLUSION
  11. Chapter 5: Ethical Tensions Emerging from the Application of the Collective Intelligence Concept in Academic Social Networking
    1. ABSTRACT
    2. INTRODUCTION
    3. THEORETICAL FRAMEWORK
    4. ETHICAL ISSUES EMERGING FROM COLLECTIVE INTELLIGENCE
    5. CONCLUSION
  12. Chapter 6: Sem-IDi
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. THE SEM-IDI APPROACH
    5. FUTURE RESEARCH DIRECTIONS
    6. CONCLUSION
  13. Chapter 7: Enterprise Tomography
    1. ABSTRACT
    2. INTRODUCTION
    3. FEDERATED ERP IN A CLOUD
    4. GOVERNANCE OF INTEGRATION LIFECYCLE MANAGEMENT IN ENTERPRISE CLOUDS
    5. SEMANTIC DEBUGGING PATTERNS
    6. FUTURE RESEARCH DIRECTIONS: INFERENCE-OPERATOR
    7. RELATED WORKS
    8. CONCLUSION
  14. Chapter 8: Semantic Web Data Partitioning
    1. ABSTRACT
    2. INTRODUCTION
    3. ISSUES IN ACCESSING SEMANTIC WEB DATA
    4. DATA PARTITIONING TECHNIQUES
    5. DATA COMPRESSION
    6. DATA CLUSTERING
    7. COMPARISON OF DATA PARTITIONING TECHNIQUES
    8. DATA PARTITIONING IN PRACTICE
    9. FUTURE DIRECTION
    10. SUMMARY
  15. Chapter 9: Metamodels Construction Based on the Definition of Domain Ontologies
    1. ABSTRACT
    2. INTRODUCTION
    3. ONTOLOGY CONCEPTS
    4. MODEL DRIVEN ENGINEERING (MDE)
    5. CONVERSION OF A DOMAIN ONTOLOGY TO METAMODEL
    6. CASE STUDY: DOMAIN SPECIFIC LANGUAGE FOR THE GENERATION OF LEARNING MANAGEMENT SYSTEMS MODULES
    7. CONCLUSION AND FUTURE RESEARCH WORK
  16. Chapter 10: Knowledge Building in Online Environments
    1. ABSTRACT
    2. INTRODUCTION
    3. COLLECTIVE INTELLIGENCE
    4. THE AFFORDANCES OF OUTSIDENESS FOR COLLECTIVE INTELLIGENCE
    5. ADAPTIVE EXPERTISE: COPING WITH THE DYNAMICS OF COLLECTIVE INTELLIGENCE
    6. CASE STUDY: ENGAGING WITH CO-CONSTRUCTION OF KNOWLEDGE
    7. CONCLUSION
  17. Chapter 11: Enhancing Information Extraction with Context and Inference
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. VISION
    5. SYSTEM ARCHITECTURE
    6. CASE STUDY
    7. DOMAIN ADAPTATION
    8. FUTURE WORK
    9. CONCLUSION
  18. Chapter 12: An Ontology-Based Search Tool in the Semantic Web
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORK
    4. AN ONTOLOGICAL-BASED APPROACH FOR CLUSTERING THE WEB META-SEARCH RESULTS
    5. THE SEARCH RESULTS CLUSTERING PROCEDURE
    6. IMPLEMENTATION OF THE ONTOLOGY-BASED SEARCH CLUSTERING SOLUTION
    7. CLUSTERING ALGORITHM IMPLEMENTATION
    8. EXPERIMENTATION AND EVALUATION
    9. FUTURE DEVELOPMENT
    10. CONCLUSION
  19. Chapter 13: Exploring Semantic Characteristics of Socially Constructed Knowledge Repository to Optimize Web Search
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORK
    4. SEMANTIC CHARACTERISTICS OF SOCIALLY CONSTRUCTED KNOWLEDGE REPOSITORY
    5. CONCEPTUAL FRAMEWORK
    6. EXPERIMENTAL RESULTS AND ANALYSIS
    7. A CASE STUDY
    8. DISCUSSION
    9. LIMITATION AND FUTURE WORK
    10. SUMMARY
  20. Chapter 14: Identifying Polarized Wikipedia Articles
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORK
    4. CAPTURING POLARITY IN WIKIPEDIA ARTICLES
    5. EXPERIMENTAL EVALUATION AND RESULTS
    6. CONCLUDING REMARKS AND FUTURE WORK
  21. Chapter 15: Ontology-Based Optimization in Search Engine
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. INDUCTIVE LEARNING
    5. LEARNING PROCESS / CRISP-DM
    6. ONTOLOGY
    7. EVALUATION
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
  22. Chapter 16: Mining Sentiment Using Conversation Ontology
    1. ABSTRACT
    2. INTRODUCTION
    3. ONTOLOGY FUNDAMENTALS
    4. EXTRACTING KNOWLEDGE FROM TEXT
    5. DISCOVERING CONVERSATION STRUCTURES
    6. CONVERSATION ONTOLOGY DRIVEN SENTIMENT MINING
    7. CONCLUSION
  23. Chapter 17: Automatic Sentiment Analysis on Web Texts for Competitive Intelligence
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORK
    4. PRESENTATION OF THE SOFTWARE TOOL
    5. THE TASK ONTOLOGY
    6. EXPERIMENTS AND EVALUATION
    7. CONCLUSION
  24. Chapter 18: Ontology-Based Opinion Mining
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. TOWARDS AN ONTOLOGY-BASED OPINION MINING
    5. FORMAL DESCRIPTION LANGUAGE
    6. A FRAMEWORK FOR ONTOLOGY-BASED OPINION MINING
    7. PREDICATE IDENTIFICATION
    8. OPINION IDENTIFICATION
    9. RESULTS
    10. FUTURE RESEARCH DIRECTIONS
    11. CONCLUSION
  25. Chapter 19: Intermediary Design for Collaborative Ontology-Based Innovation Monitoring
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. INTERMEDIARY DESIGN
    5. FUTURE RESEARCH DIRECTIONS
    6. CONCLUSION
  26. Compilation of References
  27. About the Contributors