Cover image for Applied Semantic Web Technologies

Applied Semantic Web Technologies

Author Jon Atle Gulla , Vijayan Sugumaran
Release Date: 2011/08/01
ISBN: 9781439801574
Topic:
0%
105
Chapters
0-1
Hours read
0k
Total Words
    Start Reading Now    
       Add to Wishlist       
View table of contents

Book Description

The rapid advancement of semantic web technologies, along with the fact that they are at various levels of maturity, has left many practitioners confused about the current state of these technologies. Focusing on the most mature technologies, Applied Semantic Web Technologies integrates theory with case studies to illustrate the history, current st

Table of Contents

  1. Front Cover
  2. Contents
  3. Acknowledgment
  4. Editors
  5. Contributors (1/2)
  6. Contributors (2/2)
  7. Chapter 1: Applied Semantic Web Technologies: Overview and Future Directions (1/4)
  8. Chapter 1: Applied Semantic Web Technologies: Overview and Future Directions (2/4)
  9. Chapter 1: Applied Semantic Web Technologies: Overview and Future Directions (3/4)
  10. Chapter 1: Applied Semantic Web Technologies: Overview and Future Directions (4/4)
  11. Chapter 2: Ontology: Fundamentals and Languages (1/9)
  12. Chapter 2: Ontology: Fundamentals and Languages (2/9)
  13. Chapter 2: Ontology: Fundamentals and Languages (3/9)
  14. Chapter 2: Ontology: Fundamentals and Languages (4/9)
  15. Chapter 2: Ontology: Fundamentals and Languages (5/9)
  16. Chapter 2: Ontology: Fundamentals and Languages (6/9)
  17. Chapter 2: Ontology: Fundamentals and Languages (7/9)
  18. Chapter 2: Ontology: Fundamentals and Languages (8/9)
  19. Chapter 2: Ontology: Fundamentals and Languages (9/9)
  20. Chapter 3: Toward Semantic Interoperability between Information Systems (1/5)
  21. Chapter 3: Toward Semantic Interoperability between Information Systems (2/5)
  22. Chapter 3: Toward Semantic Interoperability between Information Systems (3/5)
  23. Chapter 3: Toward Semantic Interoperability between Information Systems (4/5)
  24. Chapter 3: Toward Semantic Interoperability between Information Systems (5/5)
  25. Chapter 4: AlViz: A Tool for Ontology Alignment Utilizing Information Visualization Techniques (1/4)
  26. Chapter 4: AlViz: A Tool for Ontology Alignment Utilizing Information Visualization Techniques (2/4)
  27. Chapter 4: AlViz: A Tool for Ontology Alignment Utilizing Information Visualization Techniques (3/4)
  28. Chapter 4: AlViz: A Tool for Ontology Alignment Utilizing Information Visualization Techniques (4/4)
  29. Chapter 5: SRS: A Hybrid Ontology Mediation and Mapping Approach (1/4)
  30. Chapter 5: SRS: A Hybrid Ontology Mediation and Mapping Approach (2/4)
  31. Chapter 5: SRS: A Hybrid Ontology Mediation and Mapping Approach (3/4)
  32. Chapter 5: SRS: A Hybrid Ontology Mediation and Mapping Approach (4/4)
  33. Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (1/6)
  34. Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (2/6)
  35. Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (3/6)
  36. Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (4/6)
  37. Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (5/6)
  38. Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (6/6)
  39. Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (1/7)
  40. Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (2/7)
  41. Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (3/7)
  42. Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (4/7)
  43. Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (5/7)
  44. Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (6/7)
  45. Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (7/7)
  46. Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (1/6)
  47. Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (2/6)
  48. Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (3/6)
  49. Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (4/6)
  50. Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (5/6)
  51. Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (6/6)
  52. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (1/13)
  53. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (2/13)
  54. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (3/13)
  55. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (4/13)
  56. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (5/13)
  57. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (6/13)
  58. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (7/13)
  59. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (8/13)
  60. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (9/13)
  61. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (10/13)
  62. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (11/13)
  63. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (12/13)
  64. Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (13/13)
  65. Chapter 10: Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing (1/5)
  66. Chapter 10: Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing (2/5)
  67. Chapter 10: Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing (3/5)
  68. Chapter 10: Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing (4/5)
  69. Chapter 10: Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing (5/5)
  70. Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (1/6)
  71. Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (2/6)
  72. Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (3/6)
  73. Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (4/6)
  74. Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (5/6)
  75. Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (6/6)
  76. Chapter 12: Semantic Sentiment Analyses Based on Reputations of Web Information Sources (1/5)
  77. Chapter 12: Semantic Sentiment Analyses Based on Reputations of Web Information Sources (2/5)
  78. Chapter 12: Semantic Sentiment Analyses Based on Reputations of Web Information Sources (3/5)
  79. Chapter 12: Semantic Sentiment Analyses Based on Reputations of Web Information Sources (4/5)
  80. Chapter 12: Semantic Sentiment Analyses Based on Reputations of Web Information Sources (5/5)
  81. Chapter 13: Semantics and Search (1/7)
  82. Chapter 13: Semantics and Search (2/7)
  83. Chapter 13: Semantics and Search (3/7)
  84. Chapter 13: Semantics and Search (4/7)
  85. Chapter 13: Semantics and Search (5/7)
  86. Chapter 13: Semantics and Search (6/7)
  87. Chapter 13: Semantics and Search (7/7)
  88. Chapter 14: Toward Semantics-Based Service Composition in Transport Logistics (1/4)
  89. Chapter 14: Toward Semantics-Based Service Composition in Transport Logistics (2/4)
  90. Chapter 14: Toward Semantics-Based Service Composition in Transport Logistics (3/4)
  91. Chapter 14: Toward Semantics-Based Service Composition in Transport Logistics (4/4)
  92. Chapter 15: Ontology-Driven Business Process Intelligence (1/7)
  93. Chapter 15: Ontology-Driven Business Process Intelligence (2/7)
  94. Chapter 15: Ontology-Driven Business Process Intelligence (3/7)
  95. Chapter 15: Ontology-Driven Business Process Intelligence (4/7)
  96. Chapter 15: Ontology-Driven Business Process Intelligence (5/7)
  97. Chapter 15: Ontology-Driven Business Process Intelligence (6/7)
  98. Chapter 15: Ontology-Driven Business Process Intelligence (7/7)
  99. Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (1/6)
  100. Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (2/6)
  101. Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (3/6)
  102. Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (4/6)
  103. Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (5/6)
  104. Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (6/6)
  105. Back Cover