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Database systems for advanced applications ; Vol. 3453 ; 10th international conference, DASFAA 2005, Beijing, China, April 17-20, 2005, Proceedings
Data Stream Mining and Resource Adaptive Computation.- Purpose Based Access Control for Privacy Protection in Database Systems.- Complex Networks and Network Data Mining.- Bioinformatics.- Indexing DNA Sequences Using q-Grams.- PADS: Protein Structure Alignment Using Directional Shape Signatures.- LinkageTracker: A Discriminative Pattern Tracking Approach to Linkage Disequilibrium Mapping.- Watermarking and Encryption.- Query Optimization in Encrypted Database Systems.- Watermarking Spatial Trajectory Database.- Effective Approaches for Watermarking XML Data.- XML Query Processing.- A Unifying Framework for Merging and Evaluating XML Information.- Efficient Evaluation of Partial Match Queries for XML Documents Using Information Retrieval Techniques.- PathStack: A Holistic Path Join Algorithm for Path Query with Not-Predicates on XML Data.- XML Coding and Metadata Management.- An Improved Prefix Labeling Scheme: A Binary String Approach for Dynamic Ordered XML.- Efficiently Coding and Indexing XML Document.- XQuery-Based TV-Anytime Metadata Management.- Data Mining.- Effective Database Transformation and Efficient Support Computation for Mining Sequential Patterns.
Data Streams : Models and Algorithms
It primarily discusses issues related to the mining aspects of data streams rather than the database management aspect of streams. This volume covers mining aspects of data streams in a comprehensive style. Each contributed chapter, from a variety of well known researchers in the data mining field, contains a survey on the topic, the key ideas in the field from that particular topic, and future research directions.
Data mining and machine learning applications
Elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data.
Learning from data streams : Processing techniques in sensor networks
The book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. The set of chapters covers the state-of-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education.
