Advances in Databases 18th British National Conference on Databases, BNCOD 18 Chilton, UK, July 9-11, 2001. Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Read, Brian (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2001.
• Έκδοση: 1st ed. 2001.
• Σειρά: Lecture Notes in Computer Science, 2097
• Θέματα: Data structures (Computer science).; Database management.; Information storage and retrieval.; Application software.; Data Structures and Information Theory.; Database Management.; Information Storage and Retrieval.; Information Systems Applications (incl. Internet).

The ever-expanding growth of Information Technology continues to place fresh demands on the management of data. Database researchers must respond to new challenges, particularly to the opportunities offered by the Internet for access to distributed, semi-structured and multimedia data sources. th Th...

Πίνακας περιεχομένων:

• Invited Papers
• SEAL - A Framework for Developing SEmantic Web PortALs
• E-Science and the Grid
• Performance and Optimisation
• An Analysis of Main-Memory and Log Space Usage in Extended Ephemeral Logging
• An Effective Data Placement Strategy for XML Documents
• LOIS: The "Lights Out" Integrity Subsystem
• Objects - Design & Development
• CASE-Tool Interchange of Design Transformations
• The Real Benefits of Object-Relational DB-Technology for Object-Oriented Software Development
• Object-Oriented Versioning in a Concurrent Engineering Design Environment
• Query Optimisation
• Experiences with IR TOP N Optimization in a Main Memory DBMS: Applying 'the Database Approach' in New Domains
• Limiting Result Cardinalities for Multidatabase Queries Using Histograms
• Memory Aware Query Routing in Interactive Web-Based Information Systems
• Querying Objects
• Inferring the Principal Type and the Schema Requirements of an OQL Query
• Immersed Visual Data Mining: Walking the Walk.