Ebook: Soft Computing in Ontologies and Semantic Web
- Tags: Appl.Mathematics/Computational Methods of Engineering, Artificial Intelligence (incl. Robotics), Information Systems Applications (incl.Internet), Computing Methodologies, Applications of Mathematics
- Series: Studies in Fuzziness and Soft Computing 204
- Year: 2006
- Publisher: Springer-Verlag Berlin Heidelberg
- Edition: 1
- Language: English
- pdf
This book covers in a great depth the fast growing topic of tools, techniques and applications of soft computing (e.g., fuzzy logic, genetic algorithms, neural networks, rough sets, Bayesian networks, and other probabilistic techniques) in the ontologies and Semantic Web. How components of the Semantic Web (like the RDF, Description Logics, ontologies) can be covered with a soft computing focus is shown. The book aims to provide a single account of current studies in soft computing approaches to the ontologies and the Semantic Web. The objective of the book is to provide the state of the art information to researchers, practitioners, and graduate students of the Web intelligence, and at the same time serving the information technology professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.
This book covers in a great depth the fast growing topic of tools, techniques and applications of soft computing (e.g., fuzzy logic, genetic algorithms, neural networks, rough sets, Bayesian networks, and other probabilistic techniques) in the ontologies and Semantic Web. How components of the Semantic Web (like the RDF, Description Logics, ontologies) can be covered with a soft computing focus is shown. The book aims to provide a single account of current studies in soft computing approaches to the ontologies and the Semantic Web. The objective of the book is to provide the state of the art information to researchers, practitioners, and graduate students of the Web intelligence, and at the same time serving the information technology professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.
This book covers in a great depth the fast growing topic of tools, techniques and applications of soft computing (e.g., fuzzy logic, genetic algorithms, neural networks, rough sets, Bayesian networks, and other probabilistic techniques) in the ontologies and Semantic Web. How components of the Semantic Web (like the RDF, Description Logics, ontologies) can be covered with a soft computing focus is shown. The book aims to provide a single account of current studies in soft computing approaches to the ontologies and the Semantic Web. The objective of the book is to provide the state of the art information to researchers, practitioners, and graduate students of the Web intelligence, and at the same time serving the information technology professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.
Content:
Front Matter....Pages I-XI
Front Matter....Pages I-XI
BayesOWL: Uncertainty Modeling in Semantic Web Ontologies....Pages 3-29
Modeling Uncertainty in Semantic Web Taxonomies....Pages 31-46
A Probabilistic, Logic-Based Framework for Automated Web Directory Alignment....Pages 47-77
The SP Theory and the Representation and Processing of Knowledge....Pages 79-101
Front Matter....Pages I-XI
Dynamic Services for Open Ambient Intelligence Systems....Pages 105-122
Development of Ontologies by the Lowest Common Abstraction of Terms Using Fuzzy Hypernym Chains....Pages 123-148
Beyond the Semantic Web: Fuzzy Logic-Based Web Intelligence....Pages 149-209
An Ontology-Based Method for User Model Acquisition....Pages 211-229
On Some Problems of Decision-Making Under Uncertainty in the Semantic Web....Pages 231-246
Automatic Thematic Categorization of Multimedia Documents using Ontological Information and Fuzzy Algebra....Pages 247-274
This book covers in a great depth the fast growing topic of tools, techniques and applications of soft computing (e.g., fuzzy logic, genetic algorithms, neural networks, rough sets, Bayesian networks, and other probabilistic techniques) in the ontologies and Semantic Web. How components of the Semantic Web (like the RDF, Description Logics, ontologies) can be covered with a soft computing focus is shown. The book aims to provide a single account of current studies in soft computing approaches to the ontologies and the Semantic Web. The objective of the book is to provide the state of the art information to researchers, practitioners, and graduate students of the Web intelligence, and at the same time serving the information technology professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.
Content:
Front Matter....Pages I-XI
Front Matter....Pages I-XI
BayesOWL: Uncertainty Modeling in Semantic Web Ontologies....Pages 3-29
Modeling Uncertainty in Semantic Web Taxonomies....Pages 31-46
A Probabilistic, Logic-Based Framework for Automated Web Directory Alignment....Pages 47-77
The SP Theory and the Representation and Processing of Knowledge....Pages 79-101
Front Matter....Pages I-XI
Dynamic Services for Open Ambient Intelligence Systems....Pages 105-122
Development of Ontologies by the Lowest Common Abstraction of Terms Using Fuzzy Hypernym Chains....Pages 123-148
Beyond the Semantic Web: Fuzzy Logic-Based Web Intelligence....Pages 149-209
An Ontology-Based Method for User Model Acquisition....Pages 211-229
On Some Problems of Decision-Making Under Uncertainty in the Semantic Web....Pages 231-246
Automatic Thematic Categorization of Multimedia Documents using Ontological Information and Fuzzy Algebra....Pages 247-274
....