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Journal on Data Semantics IV: Lecture Notes in Computer Science, cartea 3730

Editat de Stefano Spaccapietra
en Limba Engleză Paperback – 12 dec 2005
• Semantics in data visualization • Semantic services for mobile users • Supporting tools • Applications of semantic-driven approaches These topics are to be understood as specifically related to semantic issues. Contributions submitted to the journal and dealing with semantics of data will be considered even if they are not within the topics in the list. While the physical appearance of the journal issues is like the books from the we- known Springer LNCS series, the mode of operation is that of a journal. Contributions can be freely submitted by authors and are reviewed by the Editorial Board. Contributions may also be invited, and nevertheless carefully reviewed, as in the case for issues that contain extended versions of the best papers from major conferences addressing data semantics issues. Special issues, focusing on a specific topic, are coordinated by guest editors once the proposal for a special issue is accepted by the Editorial Board. Finally, it is also possible that a journal issue be devoted to a single text.
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Specificații

ISBN-13: 9783540310013
ISBN-10: 3540310010
Pagini: 360
Ilustrații: XII, 344 p.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.53 kg
Ediția:2005
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Journal on Data Semantics

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Generic Relationships in Information Modeling.- EMMA – A Formal Basis for Querying Enhanced Multimedia Meta Objects.- Comparing and Transforming Between Data Models Via an Intermediate Hypergraph Data Model.- iASA: Learning to Annotate the Semantic Web.- A Survey of Schema-Based Matching Approaches.- An Overview and Classification of Adaptive Approaches to Information Extraction.- View Integration and Cooperation in Databases, Data Warehouses and Web Information Systems.- Semantic Integration of Tree-Structured Data Using Dimension Graphs.- KDD Support Services Based on Data Semantics.- Integrating the Two Main Inference Modes of NKRL, Transformations and Hypotheses.