Transactions on large-scale data- and knowledge-centered systems XI : special issue on database- and expert-systems applications / Abdelkader Hameurlain [and 5 more] (eds.).Material type: TextSeries: Serienbezeichnung | Lecture notes in computer science ; 8290. | Lecture notes in computer science. Journal subline.Publication details: Berlin : Springer, ©2013. Description: 1 online resource (viii, 126 pages) : illustrations (some color)Content type: text Media type: computer Carrier type: online resourceISBN: 9783642452697; 3642452698; 364245268X; 9783642452680Other title: Transactions on large-scale data- and knowledge-centered systems 11Subject(s): Databases | Data mining | Expert systems (Computer science) | Data mining | Databases | Expert systems (Computer science) | Computer science | Database management | Data mining | Information storage and retrieval systems | Information systems | Computer Appl. in Administrative Data ProcessingGenre/Form: Electronic books. | Ebook. Additional physical formats: Printed edition:: No titleDDC classification: 005.74/5 LOC classification: QA76.9.D37 | T73 2013Online resources: Click here to access online
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Includes bibliographical references and author index.
This, the 11th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five selected papers focusing on Advanced Data Stream Management and Processing of Continuous Queries. The contributions cover different methods for avoiding unauthorized access to streaming data, modeling complex real-time behavior of stream processing applications, comparing different event-centric and data-centric platforms for the development of applications in pervasive environments, capturing localized repeated associative relationships from multiple time series, and obtaining uniform and fresh sampling strategies over input data streams generated by large open systems containing malicious participants.
ASSIST: Access Controlled Ship Identification Streams -- The HIT Model: Workflow-Aware Event Stream Monitoring -- P-Bench: Benchmarking in Data-Centric Pervasive Application Development -- Efficient Mining of Lag Patterns in Evolving Time Series -- On the Power of the Adversary to Solve the Node Sampling Problem.