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Semantics Empowered Web 3.0 : Managing Enterprise, Social, Sensor, and Cloud-based Data and Services for Advanced Applications.

Author: Amit Sheth; Krishnaprasad Thirunarayan
Publisher: San Rafael : Morgan & Claypool Publishers, 2012.
Series: Synthesis lectures on data management.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
After the traditional document-centric Web 1.0 and user-generated content focused Web 2.0, Web 3.0 has become a repository of an ever growing variety of Web resources that include data and services associated with enterprises, social networks, sensors, cloud, as well as mobile and other devices that constitute the Internet of Things. These pose unprecedented challenges in terms of heterogeneity (variety), scale  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Sheth, Amit.
Semantics Empowered Web 3.0 : Managing Enterprise, Social, Sensor, and Cloud-based Data and Services for Advanced Applications.
San Rafael : Morgan & Claypool Publishers, ©2012
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Amit Sheth; Krishnaprasad Thirunarayan
ISBN: 9781608457175 1608457176
OCLC Number: 854968520
Notes: Semantics Empowered Physical-Cyber-Social Systems.
Description: 1 online resource (177 pages).
Contents: Preface; Role of Semantics and Metadata; Web 1.0, Web 2.0, Web 3.0; Types and Models of Semantics; Types of Semantics; Implicit Semantics; Formal Semantics; Powerful (Soft) Semantics; Applications and Types of Semantics they Exploit; Retrieval Applications: Information vs. Data; Data Mining Applications; Analytical Applications; Models of Semantics; Prescriptive Approaches Summary; Descriptive Approaches Summary; Ontology and Ontology Development; What is an Ontology?; How do we Develop an Ontology?; Class vs. Property (Attribute/Relationship); Class vs. Instance; A Word about Practice. Annotation-Adding Semantics to DataDifferent Forms of Data and their Semantics; Unstructured Data; Semi-Structured Data; Structured Data; Multimedia Data; Role of Semantic Metadata; Approaches to Adding Semantics to Data; Microformats; XLink and Model Reference; RDFa; Microdata; SA-REST: Semantically Enhancing RESTful Services and Resources; A Standards-based Approach to Specifying Extraction of RDF Triples; Summing it ALL Up; Semantics for Enterprise Data; Nature of Enterprise Content and Processing; Role of Semantics in the Enterprise; Creation of Semantic Metadata: Models and Annotations. Linking Enterprise DataSemantic Metadata in eScience; Semantic Techniques in eScience; Examples of Semantic Enterprise Applications; Semantics for Services; Nature of Web Services; Role of Semantics in Web Services; Creation of Semantic Metadata: Models and Annotations; Top-down Approach Exemplified; Bottom-up Approach Exemplified; Example Applications of Semantically Annotated Web Services; Semantics for Sensor Data; Nature of Sensor Data; Role of Semantics in Sensor Networks: Space, Time, and Theme; Creation of Semantic Metadata: Models and Annotations; Semantic Annotation; Ontologies. Semantic Sensor Network OntologyRule-based Reasoning; Querying Semantic Sensor Web; Examples of Semantic Applications; Semantics for Social Data; Nature of Social Data; Role of Semantics in Social Media; Creation/Application of Semantic Metadata: Models and Annotations; Disambiguating Entity Mentions; Identifying Entities; Robustness with Respect to Off-topic Noise; Analyzing User Comments; Aggregating Attention Metadata; Annotating and Reasoning with Social Media; The BBC SoundIndex Application; Harnessing Twitter: Twitris and Twarql Applications; Semantics for Cloud Computing. Nature of Cloud ServicesRole of Semantic Modeling in Cloud Computing; Creation and Application of Semantic Metadata: Models and Annotations; Semantics for Logical and Process Portability; Semantics for Data Modeling; Semantics for Service Enrichment; Examples of Applications; Semantics for Advanced Applications; Robust Integration of Sensors Data: Reconciling Semantic Heterogeneity; Spatio-temporal Slicing and Thematic Filtering: Achieving Scalability; Dynamic Model Creation and Update: Continuous Semantics; Role of Semantics in Web of Things (Cyber-Physical Systems).
Series Title: Synthesis lectures on data management.

Abstract:

After the traditional document-centric Web 1.0 and user-generated content focused Web 2.0, Web 3.0 has become a repository of an ever growing variety of Web resources that include data and services associated with enterprises, social networks, sensors, cloud, as well as mobile and other devices that constitute the Internet of Things. These pose unprecedented challenges in terms of heterogeneity (variety), scale (volume), and continuous changes (velocity), as well as present corresponding opportunities if they can be exploited. Just as semantics has played a critical role in dealing with data h.

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