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Databases in Networked Information Systems
4th International Workshop, DNIS 2005, Aizu-Wakamatsu, Japan, March 28-30, 2005, Proceedings
herausgegeben von Subhash BhallaInhaltsverzeichnis
- Information Interchange and Management Systems.
- Predictive Business Operations Management.
- Conversation Quantization for Conversational Knowledge Process.
- Wrapper Generation for Automatic Data Extraction from Large Web Sites.
- Efficiently Coding and Querying XML Document.
- An Interface for Web Based Access to Dynamic Contents.
- HID: An Efficient Path Index for Complex XML Collections with Arbitrary Links.
- Web Data Management Systems.
- Integration of Virtual Reality and Database System Techniques.
- From Multimedia to UniversalMedia.
- The Multimedia Semantic Web.
- Storing and Retrieving Multimedia Web Notes.
- A Searching Method Based on Problem Description and Algorithmic Features.
- Augmenting the Power of the Various Versions of LSI Used in Document Retrieval.
- Networked Information Systems: Applications.
- Networked Mining of Atomic and Molecular Data from Electronic Journal Databases on the Internet.
- Development of a Data Mining Application for Huge Scale Earth Environmental Data Archives.
- Design of Automation Systems for Web Based Courseware Using XML and XSLT.
- Towards Open Education Through Distributed and Networked Information Systems – An Experience-Based Approach.
- Exploring Web Logs with Coordinated OLAP Dimension Hierarchies.
- Networked Information Systems: Implementations.
- Policies, Models, and Languages for Access Control.
- Modelling Peer-to-Peer Data Networks Under Complex System Theory.
- Attribute-Based Access to Distributed Data over P2P Networks.
- Governing the Contract Lifecycle: A Framework for Sequential Configuration of Loosely-Coupled Systems.
- GridFS: Ensuring High-Speed Data Transfer Using Massively Parallel I/O.
- Data Management Systems.
- Improving Customer Experience via Text Mining.
- A Distributed Algorithm for Outlier Detection in aLarge Database.
- An Improved Approach to Extract Document Summaries Based on Popularity.