Web 2.0 & semantic web
著者
書誌事項
Web 2.0 & semantic web
（Annals of information systems, v. 6）
Springer, c2010
- : pbk
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
According to the W3C Semantic Web Activity [1]: The Semantic Web provides a common framework that allows data to be shared and reused across appli- tion, enterprise, and community boundaries. This statement clearly explains that the Semantic Web is about data sharing. Currently, the Web uses hyperlinks to connect Web pages. The Semantic Web goes beyond that and focuses on data and envisions the creation of the web of data. On the Semantic Web, anyone can say anything about any resource on the Web. This is fully based on the concept of semantic - notations, where each resource on the Web can have an assigned meaning. This is done through the use of ontologies as a formal and explicit representation of domain concepts and their relationships [2]. Ontologies are formally based on description logics. This enables agents and applications to reason over the data when searching the Web, which has not previously been possible. Web 2. 0 has gradually evolved from letting the Web users play a more active role. Unlike the initial version of the Web, where the users mainly "consumed" content, users are now offered easy-to-use services for content production and publication. Mashups, blogs, wikis, feeds, interface remixes, and social networking/tagging s- tems are examples of these well-known services. The success and wide adoption of Web 2. 0 was in its reliance on social interactions as an inevitable characteristic of the use and life of the Web. In particular, Web 2.
目次
Tagging and Semantics.- TagFusion: A System for Integration and Leveraging of Collaborative Tags.- Semantic Enhancement of Social Tagging Systems.- Adaptability and User Interfaces.- Adaptation and Recommendation Techniques to Improve the Quality of Annotations and the Relevance of Resources in Web 2.0 and Semantic Web-Based Applications.- Adaptive Reactive Rich Internet Applications.- Knowledge Representation and User Interfaces.- Towards Enhanced Usability of Natural Language Interfaces to Knowledge Bases.- Semantic Document Model to Enhance Data and Knowledge Interoperability.- Data Mining, Software Engineering, and Semantic Web.- Ontology-Based Data Mining in Digital Libraries.- An Assessment System on the Semantic Web.
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