Databases in Networked Information Systems [electronic resource] : 4th International Workshop, DNIS 2005, Aizu-Wakamatsu, Japan, March 28-30, 2005. Proceedings / edited by Subhash Bhalla.

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 a Large Database -- An Improved Approach to Extract Document Summaries Based on Popularity.